Versioning options can now be added to tasks Save Analysis to Library and Export Data Table to Library.

Range-based Marking

The marking framework was expanded to support a new kind of symbolic marking for selecting bounded ranges of any kind of continuous data such as time or depth. These range-based selections can then be used to drive filtering and drill-down across your analyses. Rather than selecting individual data points or categories, the new range-based marking allows you click and drag across a continuous axis to define a minimum and maximum boundary to capture all data points within the selected interval. This is a particularly powerful feature when doing intensive time series analysis and root cause investigation. To enable range-based marking, go to the Marking properties panel and select “Range-based” as your marking mode.

Note: The first iteration of Range-based marking will be limited to a single table. It will also not support the Table and Parallel Coordinate Plot visualizations. There are various enhancements planned to better handle the propagation of markings across tables and visualizations.

Accelerators

There is now a new Accelerators entry in the files and data flyout. Accelerators are use case specific template analyses that give users a quicker start in their analysis task.

Wafer Map Visualization

A wafer map visualization is now available for semiconductor manufacturing workflows. The visualization enables engineers to analyze yield, defect, process, and quality data using a dedicated wafer-centric view.

Key capabilities include:

• Wafer-aware rendering with wafer outlines, notch orientation, die grids, and cross-air.

• Multi-layer visualization of die, defect, metrology, and marker data.

• Continuous and categorical coloring of wafer measurements and classifications.

• Interactive marking, zooming, panning, and linked analysis across visualizations.

• Trellised comparison of multiple wafers.

• See the document for supported data formats, configuration options, and implementation details.

AVEVA PI Connector

Spotfire 15.0 introduces a native AVEVA PI connector that allows you to access critical time series and OT data for industrial process optimization use cases.

Access PI Data

Ability to navigate Asset Framework (AF) hierarchies to identify tags for analysis. Full access to the PI Data Archive to identify tags for import. The connector supports the creation of multiple tables with tag selections with each table having unique data retrieval settings. Searching for tags and elements using native PI search syntax is fully supported. There is also a text entry option for simply pasting a list of tags to easily find the data you are looking for.

Data Retrieval Settings

The connector has a dedicated UI for managing data retrieval settings unique to PI such as selecting retrieval mode, time ranges, intervals for resampling, and weighting for calculations. Importantly, the native PI query syntax is supported when defining the data retrieval setting parameters. These parameters can then also be mapped to Document Properties for more flexible modification of your PI queries.

User Authentication

Support for Windows Integrated Security using Kerberos for user authentication workflows to the PI and AF server.

Note: This iteration of the PI connector is import-only with on-demand queries supported. There are further enhancements planned for the connector.

Statistical Testing Functions

A set of statistical testing and distribution analysis functions has been added to the Spotfire expression language. These functions enable users to evaluate normality, compare distributions, analyze variance, and test statistical significance directly within expressions.

Key capabilities include:

• Normality testing using Anderson-Darling, Shapiro-Wilk, and Kolmogorov-Smirnov methods.

• Distribution characterization using skewness and kurtosis metrics.

• Parametric and non-parametric hypothesis testing, including t-tests, ANOVA, and Krusal-Wallis tests.

• Variance comparison using Levene and Brown-Forsythe tests.

• Distribution comparison using Kolmogorov-Smirnov tests.

The functions can be used in visualizations, calculated columns, and data transformations.

See the product documentation for the complete list of available functions and syntax.

Visual AI

Spotfire visual AI is made to help engineers and scientists understand their data faster and easier through helping them discover opportunities and problems by leveraging modern AI, machine learning and visual analytics in combination, with the governance and security required in enterprise context.

Spotfire Insight Agents

Spotfire Insight Agents automatically identifies trends, patterns and anomalies and surfaces these directly in Spotfire's interactive visualization experience, together with recommendations for next steps of analysis.
Insight Agents use information from the Spotfire Analysis, like the data and visualizations, and the customers generative AI service in order to identify findings and report them to the user, together with recommendations for next steps, making it easier and faster for engineers and scientists to analyze data and make business decisions. Insight agents help users build their analytical environment through data transformations, visualizations and advanced analytics.

Insight Panel and Insight Toolbar

Insight agents are invoked from the new Insights Panel, or from the new floating toolbar that shows up at the top of the visualization when data is marked. By pressing the insight button itself, all applicable insight agents will execute and report their findings, if any. It's also possible to click the drop down and choose exactly which insight agent to run, which is good when you know what you are looking for.

Agent Registry

Insight agents are available on the Spotfire Agent registry, available through in the add-ons browser and also through Spotfire Exchange. The Agent registry lets you browse, search and filter for Insight Agents, and easily install those that you find suitable for your needs.
Spotfire adds Insight Agents to the registry continuously, which means that new functionality is added to Spotfire 15.0 and later incrementally.

Custom Insight Agents

Spotfire continuously delivers insight agents with industry native functionality through the Agent registry. But its also possible to build your own Insight Agent, that incorporates your own business rules and knowledge, and recommendations exactly tailored to your needs. See https://github.com/spotfiresoftware/spotfire-mods for details.

AI Governance and Security

AI provides tremendous opportunities for the enterprise, but requires careful governance and security. Spotfire AI works with the AI models the customer trusts, and lets administrators configure the access to AI models for user groups. This means that customers can control who is allowed to use AI and which AI models each user group is allowed to use.
Usage of AI in general as well as token usage can monitored and audited.
Spotfire AI provides the governance, monitoring and security framework required for enterprise deployment of AI applications.

Adaptive Axes Scales

When working with continuous data, there is now a format option called Adaptive for continuous axes. The Adaptive setting adjusts the axis label time formatting to the granularity of data in the visualization to ensure the axis labels are legible and uncluttered. As you zoom into the data or apply filters, the axis labels will automatically adjust the time formatting to the appropriate context for the view. You can still see the full timestamp details by hovering over any label. This should help reduce the need for custom formatting when working with time series data.

Esri Shapefile Data Export

Spotfire supports exporting data tables containing a Well-Known Binary (WKB) geometry column directly as an Esri Shapefile (.shp). This capability simplifies spatial data transfer to external geographic information systems (GIS). GIS professionals and data analysts can seamlessly share processed spatial datasets while maintaining geographic accuracy across platforms.

Key capabilities include:

• Direct export of data tables with WKB geometry columns to .shp format

• Automatic application of the Coordinate Reference System specified in data table properties

• Fallback to WGS 84 (EPSG:4326) or the administrator-defined default projection when no system is specified

Log ASCII Standard (LAS) File Support

Spotfire now supports the direct import of Log ASCII Standard (LAS) files to simplify well log data workflows. This addition minimizes manual data preparation by automatically handling missing values and reading advanced data format specifiers. Geoscientists and engineers can immediately leverage this data to accelerate subsurface analysis without tedious manual preprocessing.

Key capabilities include:

• Bulk import of multiple LAS files simultaneously

• Support for LAS versions 1.2, 2.0, and single dataset version 3.0 files

• Extraction of well-specific metadata to facilitate geographic analysis

• Support for LAS 3.0 format specifiers using braces across file versions 1.2, 2.0, and 3.0

• Direct compatibility with the well-log visualization add-on

Probit Plot for Geologic Risk Assessment

Spotfire now includes a Probit Plot visualization to support risk and distribution analysis. This feature allows geologists and reservoir engineers to quickly quantify statistical subsurface risk and uncertainty without complex manual setup. By providing direct probability and distribution modeling, users can streamline geologic risk assessments and accelerate asset evaluation.

Key capabilities include:

• Probability scale on the vertical axis to evaluate risk profiles

• Vertical reference lines for rapid data lookup at P10, P50, and P90 percentiles

• Distribution reference lines using Q1/Q3 or least squares methods to identify outliers

• Support for normal and lognormal distributions and configurable P10/P90 directions

Arps Decline Curve Analysis for Production Forecasting

Spotfire adds Arps decline curve modeling to support production forecasting and reserves estimation directly within visual analytic workflows. This capability allows reservoir engineers and data analysts to model asset depletion stages. By integrating decline curve analysis into core visualizations, users can evaluate well performance dynamically alongside other operational metrics.

Key capabilities include:

• Support for exponential, hyperbolic, and harmonic Arps equations to model various reservoir depletion stages

• Configurable parameter constraints and terminal exponential decline limits to prevent overestimating reserves

• Automated, interactive reserves calculations that update dynamically based on data filtering and marking

• Trellis visualization support to view and compare multiple well decline curves simultaneously on a single page

• Direct export of calculated curve points, fitted parameters, and reserves results to data tables

Reference elements improvements

Reference elements now support richer visualizations with even more control over your reference layers. Users can now create reference layers with:

• Data tables that are independent of the top-level visualization 

• Categorical groupings that are independent of the top-level visualization

• Unique styling and color-by configurations specific to each layer

With these improvements to reference elements, there are no limitations to the density of data and contextual information that can be layered on a single visualization.

Push Compute on Snowflake and Databricks

Spotfire 15.0 adds push compute capabilities to execute analytics and data transformations directly within the Snowflake and Databricks data platforms. Users can perform large-scale analysis without moving data out of the platform while continuing to use familiar Spotfire workflows.

Key capabilities include:

• Secure Single Sign-On access using individual user credentials

• In platform execution of data canvas transformations including pivots, unpivots, joins, and calculated columns

• Data functions operating directly on data that is within the platform using optimized, parallelized analysis libraries.

• Bidirectional data movement to upload local data for scalable compute or download results for high-speed interaction

See the Push Compute documentation for implementation details and supported functionality

Expanded Statistica Data Function Algorithms

Spotfire expands its no-code analytical capabilities with 17 additional Statistica algorithms, bringing the total library to 40 available methods when the Statistica Integration is deployed. The system automatically generates data function definitions when adding these algorithms, facilitating advanced statistical analysis and machine learning workflows directly within the visual workspace. This integration allows users to configure and execute complex data science models seamlessly without writing custom code.

Newly added algorithms include:

• Normality Testing by Groups

• Partial Least Squares Classification & Regression Model Training and Scoring

• Advanced Feature Selection

• Lasso Linear & Logistic Regression

• Model Comparisons for Classification & Regression

• Sparse Data Filtering

Copy descriptions for input and output parameters from the Edit Parameters dialog for data functions

You can now copy the descriptions of input and output parameters for a data function to the clipboard by right-clicking the description field in the Edit Parameters dialog, and selecting Copy description. This can be useful to be able to read long descriptions that do not fit in the tooltip.

Limit curve fit to marked rows

There is a new setting for Lines and Curves that when enabled performs curve fitting on only the currently marked data in a visualization. This feature is by default off, and can configured from the new visualization properties panel.

New statistical functions available: BetaDist, BetaInv, KSDist and KSInv

The following statistical functions have been added to the Spotfire expression language:

• BetaDist – calculates the probability given a quantile from the Beta(alpha,beta)-distribution

• BetaInv – calculates the quantile of the Beta(alpha,beta)-distribution for a given probability

where alpha and beta are the scale parameters of the underlying Beta distribution.

• KSDist – calculates the probability given a quantile from the KS(d,n)-distribution

• KSInv – calculates the quantile of the KS(d,n)-distribution for a given probability

where d is the distance statistic and n is the number of observations of the underlying Kolmogorov-Smirnov distribution.

Show minor gridlines for logarithmic scales

If you use logarithmic scales in visualizations, Spotfire now shows additional minor gridlines by default. This setting can be controlled by a new preference and it can also be configured in the visualization properties panel, for all axes that support logarithmic scales.

Configurable pruning of the undo stack

To reduce the amount of storage used by the undo stack, Spotfire can now prune old items from the stack. This behavior is controlled by the new application preferences Prune undo stack and Prune undo stack limit (minutes), found under Application > Undo stack in the Administration Manager. By default, the undo stack remains unlimited.

New paging option for trellis panels

When you work with trellised visualizations, you can now split trellis panels further, using the new Pages option.

If you are working as an engineer with wafer-centric semiconductor workflows, and you routinely review complete lots and expect all wafers from the same lot to be shown together, you can use this functionality to page trellis panels by lot. This way, you can review lots sequentially, reduce visual clutter, and avoid misinterpretation during yield, defect, and process investigations.

Page-based trellising benefits any analysis where you review dense panel grids one logical group at a time, such as batch analysis, unit comparison, product families, or segmented operational data across industries.

The new option, Pages, is available on the Trellis by card in the Visualization properties panel if you select Panels in the drop-down list at the top. Previously, Pages was only available for the Rows and columns option.

SAP HANA data connector improvements

You can now make use of a range of new features when you connect to your SAP HANA databases:

Access data from SAP HANA in the web client

You can now create new SAP HANA data connections in the web client. You can also edit existing connections. This makes it easier to use data from your SAP HANA databases when you author analyses in the web client.

Note: Some connection authoring capabilities, such as writing custom queries, are only available when you use the installed client. For details, see the documentation.

Modernized look

The data connector for SAP HANA has a new and improved user interface for connecting to your databases, the Select data flyout.

New Statistics layer for showing calculated metrics in visualizations

A new layer type, called Statistics layer, has been introduced in all visualizations that have a continuous X- or Y-axis.

This new type of reference layer lets you present any calculated statistics directly within the visualization. These measures can be defined using expressions or data from either the current data table, or from a related table. The numbers can be positioned in line with the visualization, or placed wherever you want, with full customization of alignment, size, padding, categorization, and trellis layouts, providing a flexible way to surface key metrics and contextual statistics in the visualization.

Enhanced reference elements: Category-by support on continuous x-axis

Reference elements now support the category-by configuration even when the top-level visualization uses a continuous axis such as time or numeric values. Users can now:

• Add category-driven reference lines, points, bands, and measures to visualizations with continuous x-axis.

• Define dynamic thresholds, targets and benchmark along the axis.

• Overlay multiple context-specific reference elements on times series and other continuous axes.

• Build richer comparative and process monitoring visualizations without restructuring data.

This improvement significantly expands the analytical flexibility of reference elements across many use cases. By removing the need for artificial binning or categorical restructuring, this update allows continuous data to remain continuous while still benefiting from reference layers.

.NET 10 support for Spotfire services on Linux

Microsoft .NET 10 is now supported for:

• Spotfire Web Player

• Spotfire Automation Services

when running Spotfire on a supported Linux distribution (Debian, Ubuntu, Red Hat Enterprise Linux).

Note: You might need to compile and validate your .NET based custom extensions. For more information, see Extensions, in the Spotfire Developer Documentation.

Note: The support for .NET 8 has now been removed.

Dependent data views in visualization mods

As a mod developer, you can now declare one data view as dependent on another, retrieve detailed data scoped to a specific parent row or category, and rely on the mods framework to automatically manage axis alignment and data scoping.

This makes it possible to create advanced visualizations, such as graphical tables with embedded charts, summary-and-detail views within a single visualization, and stable multi-layer composite visualizations.

Framework-managed dependencies lead to predictable behavior when the configuration changes in a visualization mod, and reduces the need for custom synchronization logic to build complex and expressive visualizations.

Multiple dynamic data views in visualization mods

Dynamically created data views are now supported in visualization mods, which makes it possible to create fully user-driven, multi-layered visualizations, combining static and dynamic data views.

With this new feature, visualization mods are no longer limited to a fixed set of predefined data views. Instead, as a mod developer, you can define layer types, and as an analyst, you can dynamically add, remove, and configure layers at runtime, each layer backed by its own independent data view and connected to any data table in the analysis.

You can create mods that mix foundational layers with optional analytical overlays, and with support for data bindings, markings, and configuration options.

Marking data from trellis headers

It is now possible to mark all data within a trellis panel or page by clicking the panel/page header. To mark data in multiple panels at once, you can use Ctrl + click.

This capability significantly accelerates workflows where you compare many dense panels side by side. For example, when analyzing wafer maps and defect maps in semiconductor manufacturing, but also in batch analysis, unit comparison, regional breakdowns, and for other high-density trellised views.

Spotfire SBOM files now available from the downloads site

SBOM files (Software Bill of Materials) are now included with the products available on the Spotfire download site. The SBOM files list the included third party software components, versions, and licenses.

The SBOMs are delivered as SPDX (System Package Data Exchange) standard files (ISO/IEC 5962:2021). This is a machine-readable format for exchange of software license information.

Contextual visualization properties panel becomes the default authoring experience

Starting with Spotfire 14.8, the contextual visualization properties panel becomes the sole experience used for configuring visualizations in the web client, and it also becomes the default option in the installed client (with the dialog still available where applicable). This milestone marks the completion of a transition over multiple releases to a modern, contextual, and scalable visualization authoring experience.

Over the past months, you have been able to explore the new panel alongside the classic properties dialog/popover, provide feedback, and continue using all existing capabilities without disruption. With Spotfire 14.8, the legacy web properties popover is now fully replaced by the new experience, providing web client authors with a consistent, efficient, and future-proof way to configure visualizations.

Authors using the installed Windows client can still switch to the classic properties dialog from the Visualizations menu. An administrator can also change the Default to contextual visualization properties panel preference to False in the Administration Manager under Application > ApplicationPreferences.

Teradata connector improvements

The data connector for Teradata has received an overhaul. You can now make use of a range of new features when you connect to your Teradata databases:

Access data from Teradata in the web client

You can now create new data connections in the web client. You can also edit existing connections. This makes it easier to use data from your Teradata databases when you author analyses in the web client.

Note: Some connection authoring capabilities, such as writing custom queries, are only available when you use the installed client. For details, see the documentation.

Custom properties in connection data sources

When you create a data connection, you can now configure settings in the driver software that the data connector does not have built-in properties for. Custom properties can be useful for tweaking the connection performance, changing the behavior of a connection, or accessing certain data.

Statistica algorithms available in the installed Spotfire Industry Pro client

Twenty-three no-code Statistica algorithms are now directly available in the installed Spotfire Industry Pro client, if the Spotfire Statistica Integration is deployed in your system. Data function definitions for the Statistica algorithms are automatically generated when you add algorithms to your analysis, for advanced statistical analysis and machine learning analyses. You find them under Tools > Statistica > Algorithms.

The data functions can be configured in different Spotfire workflows to provide data transformations, classic statistics, correlations, machine learning, training/scoring for regression and classification, as well as time series analysis, and statistical quality control. The data functions have default configurations for common usage patterns, but also offer a rich set of advanced parameters that you can customize to solve sophisticated analysis problems.

Updated design on the landing page and Learn and discover flyout

New cards on the landing page and the Learn and discover flyout will now get a label indicating that they are new.

Browser GPU information in the Support Diagnostics and Logging dialog

A new tab showing browser GPU information for the CEF (Chromium Embedded Framework) is now available in the Support Diagnostics and Logging dialog, providing a useful supplement to the Browser Information tab.

This information is available in the installed client under Help > Support diagnostics and logging, on the Browser GPU Information tab.

Visual identification of added columns

When you are working with wide data sets, your analyses might rely on calculated and other inserted columns, created within your Spotfire analysis. In some earlier releases, these columns were not visually distinguishable from imported columns in the Data in analysis flyout, making it difficult to quickly find and edit these columns, or to understand the origin of the columns.

In Spotfire 14.8 (and Spotfire 14.6.2), inserted columns are now clearly identified in the Data in analysis column list, using icons. You can immediately recognize which columns were created in Spotfire versus those that are coming from the data source.

This improvement restores clarity for you who work extensively with calculated columns, while reinforcing the new workflow and reducing friction during the transition from an earlier column management experience.

Nested aggregations in reference elements

The value expression and the secondary value expression of a reference layer now support nested aggregations when you are working with imported data.

Load third-party AddIns in separate AssemblyLoadContexts

Third-party extensions can now enable assembly isolation mode when building for .NET, by adding the /loadisolated argument to the Package Builder console when you are building packages. The mode can also be enabled by adding a LoadIsolated="true" attribute to the PackageDescription element in the .pkdesc file.

For more information about this feature, see the Spotfire Developer Documentation.

Add columns from the Data in analysis flyout

When you are preparing your data, this often involves a tight loop of creating, reviewing, and refining calculated or derived columns.

Previously, inserting new columns required you to leave the Data in analysis flyout which interrupted your workflow and made column-related tasks feel fragmented compared to earlier experiences.

In Spotfire 14.8 (and Spotfire 14.6.2), you can now add calculated and binned columns, as well as hierarchies, directly from the Data in analysis flyout, without leaving the flyout.

This enhancement consolidates column-related tasks into a single, focused workspace. This way, you can improve your efficiency and reduce context switching, especially if you frequently create and refine derived columns as part of your analysis.

Sort columns by type in the Data in analysis flyout

As analyses grow, column lists often include a mix of imported, calculated, binned, and other column types. Previously, you could not easily group or prioritize these columns in the Data in analysis flyout, making it difficult to quickly locate the columns you have created yourself during analysis.

In Spotfire 14.8, columns in the Data in analysts flyout can now be sorted by column type, making derived columns immediately findable, without having to switch to the data canvas.

This enhancement improves efficiency when you are working with wide data sets, reinforces clarity in the new column management experience, and further reduces friction during the transition from earlier workflows.

CLI command to re-sign mods

The new CLI command, re-sign-mod, allows administrators to update the digital signature of mods, which can either be stored in the library or local .mod files, using a designated user account.

This capability makes it easier to migrate mods between Spotfire environments (such as development, test, production) without complex cross-server certificate configurations. It also allows for centralizing trust management to a single, consistent signature, eliminating the complexity of managing individual developer signatures that might have become disabled or removed.

Learn & discover flyout

On the new Learn & discover flyout you can find Spotfire related news, events, tips, and tricks, as well as useful links to Spotfire support, the community, and the user guide. The cards on the flyout will change over time, and are the same as the cards shown on the landing page when you start Spotfire, but can be reached also when you are working with an analysis.

You can open the flyout from Help > Learn and discover flyout.

Dedicated data connector for Databricks

There is now a dedicated data connector for accessing data from Databricks.

In earlier versions, you would use the connector for Apache Spark SQL to connect to Databricks, but all the relevant functionality is now available in the stand-alone connector for Databricks. The new connector makes the process of accessing your data from Databricks more streamlined and includes the ability to browse and select data from different catalogs and schemas in the same connection.

Any existing Databricks data connections created with the connector for Apache Spark SQL continue to function. To switch to using the new connector, you must replace your existing data connections with ones that you create with the Databricks connector, by using Replace data source in your analyses.

Note: Data connections that you create with the Databricks connector cannot be opened in a Spotfire version earlier than 14.6.1.

Multiple data views in visualization mods

A flexible multi-view data model is now available for visualization mods, removing the previous limitation of a single data view per mod.

This update makes it possible to develop highly advanced, composite, and domain-specific visualizations that let you work with and present data from multiple independent sources simultaneously. For example, you can create a combination chart by merging two or more different visualization types into one mod, or create a network chart that shows nodes and edges from separate data tables.

Each data view can easily be configured and connected to any data table in the analysis (including the data table used by other views), thereby bypassing the need for manual pre-processing steps like complex table joins.

Show all data points in box plot

You can now show all underlying data points as individual markers directly in the visualization. This enhancement lets you show raw data alongside statistical summaries, which makes it easier to see distributions, identify outliers, and choose specific data points for more detailed analysis. You can customize the appearance of markers (size, transparency, and jittering). This enhancement supports large data sets and trellised views, while maintaining performance and readability in the visualization.

Vertical orientation of line chart and combination chart

You can now show a line chart and a combination chart vertically, for a natural visualization of depth-oriented and height-based data, such as geological- or reservoir-measurements. The independent variables, like depth or height, are then plotted along the vertical axis, and the measurements are plotted on the horizontal axis. The vertical orientation supports all current chart features, which includes settings for multiple scales, reference elements, curve fitting, area fills, and split by categories. 

This functionality can be configured using the API through the Orientation property available on the LineChart and CombinationChart instances.

SAP HANA data connector improvements

Modernized look

The data connector for SAP HANA has a new and improved user interface for connecting to your databases.

Custom properties in connection data sources

When you create a data connection, you can now configure settings in the driver software that the data connector does not have built-in properties for. Custom properties can be useful for tweaking the connection performance, changing the behavior of a connection, or accessing certain data.

IBM DB2 data connector improvements

The data connector for IBM DB2 has received an overhaul. You can now make use of a range of new features when you connect to your IBM DB2 databases:

Access data from IBM DB2 in the web client

You can now create new data connections in the web client. You can also edit existing connections. This makes it easier to use data from your IBM DB2 databases when you author analyses in the web client.

Note: Some connection authoring capabilities, such as writing custom queries, are only available when you use the installed client. For details, see the documentation.

Modernized look

The data connector for IBM DB2 has a new and improved user interface for connecting to your databases.

Custom properties in connection data sources

When you create a data connection, you can now configure settings in the driver software that the data connector does not have built-in properties for. Custom properties can be useful for tweaking the connection performance, changing the behavior of a connection, or accessing certain data.

Choose your default visualization properties experience

You can now choose whether to use the contextual visualization properties panel or the classic visualization properties dialog as the default experience when working with visualizations.

Administrators can set the global default using the Default to contextual visualization properties panel preference, available in the Administration Manager under Application > ApplicationPreferences. If nothing is specified, the dialog will remain the default.

Authors can also specify their personal default in Tools > Options > Application, or by opening Visualizations > Visualization properties, and selecting Default to dialog or Default to contextual panel.

No matter which default you choose, you can still access both interfaces at any time:

• The contextual panel from View > Visualization properties panel.

• The dialog (or popover in the web client) from Visualizations > Visualization Properties > Open visualization properties dialog.

Notifications from built-in data functions

If you have access to the Spotfire Data Science license, and you use the built-in data functions, you will now get more information about the specified parameters and the result of the operations in notifications.

For example:

• For built-in data functions based on geometry data, you will get a warning if your data contains any invalid or empty coordinate or geometry values (either before or after the transformation).

• For the built-in data functions CRS transformation for coordinates and CRS transformation for geometries, you get an information notification if the specified source CRS and the target CRS are identical.

• For Time series smoothing, you will see a warning if the smoothing level becomes automatically adjusted to the number of rows in the selected column (this happens when the specified smoothing level is larger than the number of rows in the input data).

Legend support for reference elements

Information about reference elements can now be shown in the visualization legend. Each reference layer is automatically listed with its configured label. This helps you identify what each reference line, band, box, or marker represents. If you have a reference layer that contains multiple reference elements, such as both markers and a line, then the legend will show that as a single legend item.

The legend functionality can be configured using the ReferenceLayer.Legend property in the API.

Tooltip support for reference elements

You can now configure tooltips for all reference element types (lines, bands, boxes, and markers). When you hover over a reference element, the tooltip shows values that can be defined from expressions or data columns. The tooltip content can come either from the visualization's data table or from a separate data table. The tooltip behavior is consistent with existing visualization configurations, including the settings on split by, color by, and trellis.

The tooltip functionality can be configured using the ReferenceLayer.Details property in the API.

Extended API functionality for progress and sub-tasks

A new API method, ExecuteWithProgressOrSubtask, has been introduced, to provide a greater flexibility when managing tasks.

• Previously: The ExecuteWithProgress method could only be used to start main progress tasks, making it impossible to initiate sub-tasks via the API.

• Now: The new ExecuteWithProgressOrSubtask method allows you to start and handle both main progress tasks and their associated sub-tasks.

Support for TLS 1.3

Spotfire clients now support TLS 1.3, provided that this has been enabled on the server, and that the client operating system supports TLS 1.3.

Expanded Statistica Data Function Algorithms

Spotfire expands its no-code analytical capabilities with 17 additional Statistica algorithms, bringing the total library to 40 available methods when the Statistica Integration is deployed. The system automatically generates data function definitions when adding these algorithms, facilitating advanced statistical analysis and machine learning workflows directly within the visual workspace. This integration allows users to configure and execute complex data science models seamlessly without writing custom code.

Newly added algorithms include:

• Normality Testing by Groups

• Partial Least Squares Classification & Regression Model Training and Scoring

• Advanced Feature Selection

• Lasso Linear & Logistic Regression

• Model Comparisons for Classification & Regression

• Sparse Data Filtering

Copy descriptions for input and output parameters from the Edit Parameters dialog for data functions

You can now copy the descriptions of input and output parameters for a data function to the clipboard by right-clicking the description field in the Edit Parameters dialog, and selecting Copy description. This can be useful to be able to read long descriptions that do not fit in the tooltip.

Spotfire SBOM files now available from the downloads site

SBOM files (Software Bill of Materials) are now included with the products available on the Spotfire download site. The SBOM files list the included third party software components, versions, and licenses.

The SBOMs are delivered as SPDX (System Package Data Exchange) standard files (ISO/IEC 5962:2021). This is a machine-readable format for exchange of software license information.

Statistica algorithms available in the installed Spotfire Industry Pro client

Twenty-three no-code Statistica algorithms are now directly available in the installed Spotfire Industry Pro client, if the Spotfire Statistica Integration is deployed in your system. Data function definitions for the Statistica algorithms are automatically generated when you add algorithms to your analysis, for advanced statistical analysis and machine learning analyses. You find them under Tools > Statistica > Algorithms.

The data functions can be configured in different Spotfire workflows to provide data transformations, classic statistics, correlations, machine learning, training/scoring for regression and classification, as well as time series analysis, and statistical quality control. The data functions have default configurations for common usage patterns, but also offer a rich set of advanced parameters that you can customize to solve sophisticated analysis problems.

Visual identification of added columns

When you are working with wide data sets, your analyses might rely on calculated and other inserted columns, created within your Spotfire analysis. In some earlier releases, these columns were not visually distinguishable from imported columns in the Data in analysis flyout, making it difficult to quickly find and edit these columns, or to understand the origin of the columns.

In Spotfire 14.8 (and Spotfire 14.6.2), inserted columns are now clearly identified in the Data in analysis column list, using icons. You can immediately recognize which columns were created in Spotfire versus those that are coming from the data source.

This improvement restores clarity for you who work extensively with calculated columns, while reinforcing the new workflow and reducing friction during the transition from an earlier column management experience.

Add columns from the Data in analysis flyout

When you are preparing your data, this often involves a tight loop of creating, reviewing, and refining calculated or derived columns.

Previously, inserting new columns required you to leave the Data in analysis flyout, interrupting this workflow and making column-related tasks feel fragmented, compared to earlier experiences.

In Spotfire 14.8 and Spotfire 14.6.2, you can now add calculated and binned columns, as well as hierarchies, directly from the Data in analysis flyout, without leaving the flyout.

This enhancement consolidates column-related tasks into a single, focused workspace, improving efficiency and reducing context switching, especially if you frequently create and refine derived columns as part of your analysis.

Updated design on the landing page and Learn and discover flyout

New cards on the landing page and the Learn and discover flyout will now get a label indicating that they are new.

Load third-party AddIns in separate AssemblyLoadContexts

Third-party extensions can now enable assembly isolation mode when building for .NET, by adding the /loadisolated argument to the Package Builder console when you are building packages. The mode can also be enabled by adding a LoadIsolated="true" attribute to the PackageDescription element in the .pkdesc file.

Learn & discover flyout

On the new Learn & discover flyout you can find Spotfire related news, events, tips, and tricks, as well as useful links to Spotfire support, the community, and the user guide. The cards on the flyout will change over time, and are the same as the cards shown on the landing page when you start Spotfire, but can be reached also when you are working with an analysis.

You can open the flyout from Help > Learn and discover flyout.

Dedicated data connector for Databricks

There is now a dedicated data connector for accessing data from Databricks.

In earlier versions, you would use the connector for Apache Spark SQL to connect to Databricks, but all the relevant functionality is now available in the stand-alone connector for Databricks. The new connector makes the process of accessing your data from Databricks more streamlined and includes the ability to browse and select data from different catalogs and schemas in the same connection.

Any existing Databricks data connections created with the connector for Apache Spark SQL continue to function. To switch to using the new connector, you must replace your existing data connections with ones that you create with the Databricks connector, by using Replace data source in your analyses.

Note: Data connections that you create with the Databricks connector cannot be opened in a Spotfire version earlier than 14.6.1.

Support for TLS 1.3

Spotfire clients now support TLS 1.3, provided that this has been enabled on the server, and that the client operating system supports TLS 1.3.

Support for ODBC Driver for Apache Arrow Flight SQL in Dremio connector

The connector for Dremio now supports using the ODBC Driver for Apache Arrow Flight SQL, to access data from Dremio versions 22.0 and later. 

Spotfire Data Science license now available with legacy licensing

You can now assign the new Spotfire Data Science product license to users, even when your Spotfire environment is configured for the legacy product licenses. This means that, in addition to Spotfire Analyst, Spotfire Business Author, and Spotfire Consumer, you can also assign Spotfire Data Science licenses and make use of powerful data science features and functionality.

Note: To use the Spotfire Data Science license, you must have an active license agreement that includes the Spotfire Data Science license. Reach out to your Spotfire sales person to learn more.

Match data tables on (Column Names)

A new option is available for column matching, making it easier to connect your data from different data tables in Spotfire. You can now effortlessly link "tall" tables—which store parameters, business rules, targets, or thresholds—with "wide" tables with many columns containing your measurements.

Instead of manually reshaping your data or hard-coding column references, you can now match a column containing column names (for example, "Temperature" or "Pressure") with the corresponding columns in another table. This is especially useful in industries where thresholds and targets are managed independently of raw data.

With this new option, you can:

• Integrate data seamlessly: Connect metadata tables to measurement tables without manual data manipulation.

• Drive analyses with metadata: Apply control limits, KPI targets, and other rules defined in separate tables directly to your sensor or production data.

• Create dynamic visualizations: Use expressions like [Axis.Y.Column] to reference the column used in a visualization. This enables flexible comparisons and calculations, keeping your visualizations automatically aligned as business rules evolve.

Filtering in the Add-ons and Demos browsers

When you browse for assets in the Add-ons or Demos browsers, you can now add filters to limit the number of assets shown in the browser. This makes it easier to find all assets related to, for example, energy, data preparation, yield optimization, etc.

Continuous updates on the landing page

The landing page, shown when you start Spotfire, now shows Spotfire related news, events, tips, and tricks. The content on the landing page will change over time to stay relevant. The continuously updated landing page will make it easier for you to keep up to date with new Spotfire capabilities, training material, webinars, and other related content.

Note: If you use cobranding on the landing page, no dynamic content will be shown.

Statistics table for box plot with expression-based measures

An enhanced version of the statistics table for the box plot is now available, giving you more flexibility when calculating statistical measures. It supports expression-based statistical measures, and lets you define and show custom calculations without the need to modify the underlying data table.

The new statistics table opens up powerful new possibilities for engineers and scientists who need to track domain-specific metrics—such as yield rates, defect percentages, or process-specific thresholds—within the context of a familiar box plot.

In addition to supporting custom expressions, the statistics table can now be shown or hidden on demand, giving you full control over the visual layout of your analysis. 

The new statistics table can be configured in the Statistics table card in the visualization properties panel.

Important: If you have configured a box plot using a previous version of the statistical measures settings, you must convert the measures to expressions to use them in the new Statistics table card. To learn more, see Adding measures to the statistics table.

Change the orientation of scale labels in the box plot

It is now possible to configure scale labels on the Category axis of the box plot. You can choose to show them horizontally or vertically, as well as to show or hide them.

This makes it easier to read dense box plots when, for example, comparing yield across production lines, defect rates by tool, or process variability across products. The vertical orientation of the labels prevents long or numerous category labels from overlapping and optimizes screen estate.

You can change the label configuration from the visualization properties or the contextual menu on the axis.

Violin plot in box plot visualization

If you have the Spotfire Data Science license, you can now turn a box plot into a violin plot by adding a kernel density estimate (KDE) around each box, and get a more nuanced view of your data. 

This functionality lets you show the probability density distribution (the shape) of data and helps you see whether data is skewed, multimodal, or exhibit unexpected patterns; critical insights that are often hidden when investigating quartiles or medians of a simple box plot only. 

Violin plots are particularly valuable for engineers and scientists working with complex or noisy data sets, such as those in manufacturing, life sciences, or with natural resources. For example, violins can enable process engineers to better understand the variation in yield or defect rates, help quality analysts detect distribution shifts in batch performance, and allow reservoir engineers to explore how performance data is distributed beyond basic summary statistics. These insights support faster troubleshooting, better decision-making, and more effective communication of findings.

You add the Violin to an existing box plot (vertical or horizontal) from the visualization properties panel, where you can also change how the bandwidth is calculated, as well as update things like the color and transparency.

Add reference elements to your visualizations

Reference elements are versatile, data-driven tools that enrich visualizations with added context. They include lines, bands, boxes, and markers that can place targets, control limits, and acceptance ranges directly within your visualizations. These elements are calculated from expressions, which can be based on data from the same table as the visualization or from a separate data table. Like the visualization, you can choose to split the reference elements by category, color, or apply trellising.

You can use reference elements for a variety of needs, including:

• Setting limits & targets (lines): Add horizontal or vertical lines to your visualizations to show specification limits, control limits, or goals for each tool, production line, or segment.

• Showing acceptable ranges (bands): Use colored bands to visualize the area between lower and upper bounds, which is useful for seeing "pass/fail" windows.

• Highlighting intervals of interest (boxes): Use boxes to highlight specific time intervals, such as production shifts or maintenance periods, or to emphasize important value windows.

• Showing benchmarks & trends (markers): Place markers on your visualizations to represent medians, averages, or other key measures. You can also connect them with lines to show trends.

This makes it easier to create metadata-driven dashboards. Now, you can use a "wide" table of your core measurements, like sensor readings, and connect it to "tall" tables that contain auxiliary information like rules or targets. This also scales to your specific context, automatically applying per plant, tool, line, lot, or customer segment. With clear labels and styling, the dashboards are presentation-ready for both data exploration and polished analytics applications.

This feature is available with the Spotfire Data Science license.

Read more in the Spotfire User Guide.

Horizontal box plot 

You can now choose to show box plots horizontally, for a more flexible way to visualize your data. This makes it easier to read long category labels and use screen space more efficiently. In many analytical workflows—such as when comparing yields across production lines, defect rates by machine, or,  when analyzing process variations across products—labels can become difficult to read with a standard layout. 

You can switch between a vertical and horizontal orientation from the visualization properties, or using the context menu. When long category names are no longer truncated and all information remains visible, even in dense, data-rich environments, the visualizations provide more key context. 

This feature is available with the Spotfire Analytics and Spotfire Data Science licenses.

Vertica data connector improvements

The data connector for Vertica has received an overhaul. You can now make use of a range of new features when you connect to your Vertica databases:

Access data from Vertica in the web client

You can now create new data connections in the web client. You can also edit existing connections. This makes it easier to use data from your Vertica databases when you author analyses in the web client.

Note: Some connection authoring capabilities, such as writing custom queries, are only available when you use the installed client. For details, see the documentation.

Custom properties in connection data sources

When you create a data connection, you can now configure settings in the driver software that the data connector does not have built-in properties for. Custom properties can be useful for tweaking the connection performance, changing the behavior of a connection, or accessing certain data.

Identity provider authentication

You can now use an identity provider for authentication in data connections to Vertica.

With the Identity provider (OAuth2) authentication method, you can enable a convenient and secure login experience for accessing only the data you have permission to access. To learn more, see Single sign-on with an identity provider (OAuth2) for connectors.

Visualization mods enhancements

The following improvements are available for visualization mods:  

Improved error logging

Visualization mod errors that are thrown in readable callbacks are now logged as errors, to make debugging easier.

Optional axes

Visualization mod developers can now declare an axis as "optional", which means that the axis will only be shown in the visualization properties panel when the axis is configured.

Geographical and complex data type support for Vertica connections

In Vertica data connections, you can now access the following data types:

• Geography

• Geometry

• Array

• Row

• Set

Easier to use many built-in data functions

Several of the input parameters for the built-in data functions are now easier to specify, using options in drop-down lists instead of simple text fields.

Easier to select a Coordinate Reference System in built-in data functions

The geographic built-in data functions now use the same Coordinate Reference System (CRS) selector as the map chart. Click Select CRS next to the Value input field to open a dialog where you can get more information in tooltips and choose the CRS to use directly.

New SSL settings for Cloudera Impala data connections

Two new data source properties, Allow self-signed certificate and Allow common name host name mismatch, have been added for the Cloudera Impala data connector.

Spotfire username as delegated user in Cloudera Impala data connections

A new data source property, Use Spotfire username as delegated user, is available for data connections to Cloudera Impala. With this property, you can configure a data connection so that the username of the logged in Spotfire user is used as the delegated user (DelegationUID) in the Cloudera Impala system.

Use system trust store setting for Apache Spark SQL data connections

A new data source property, Use system trust store, is available for the Apache Spark SQL connector. With this property, you can configure data connections to use the trusted certificates in the system trust store on the computer running Spotfire to verify the server identity when you use SSL.

Timeout preferences for TIBCO Data Virtualization data connections

You can now control the command and connection timeouts for TIBCO Data Virtualization data connections. To set the timeouts, use the new preferences CommandTimeout and ConnectionTimeout under Connectors > TIBCO Data Virtualization.

Vertica connector support on Linux Web Player services

You can now use the data connector for Vertica in the web client when the Web Player service is running on a Linux computer.

Note: For use on Linux computers, the Vertica driver must be packaged and deployed as a .spk package. See the driver installation instructions.
 

Identity provider authentication (OAuth2) in Oracle data connections

You can now use an identity provider for authentication when you create data connections with the connector for Oracle. With this new authentication method, you can use the Oracle integration with Microsoft Entra ID (formerly Azure AD) as the identity provider in Oracle data connections.

Built-in data functions provided with Spotfire Data Science

Nine new data functions covering time series, geoanalytics, and missing data analysis are now included with the Spotfire Data Science license, both in the installed client and in the web client. They can be added to your analysis from the f(x) flyout:

• Time series resampling: Returns a resampled version of the provided data table or columns containing time series data.

• Time series smoothing:  Returns a smoothed version of the provided numerical measurement column, where variations in the data (peaks) have been cut. You can choose from Friedman's supersmoother, LOESS (Locally Estimated Scatterplot Smoothing), or a simple exponential smoothing.

• Dynamic time warping:  Applies dynamic time warping (DTW) which can be used to compare a set of sequences to a reference sequence, and find similarities between patterns even if the sequence lengths are different.

• Missing data summary:  Provides a summary of all missing (invalid) values from the input data in the form of three output data tables; 'Missing data (MD) – Summary of input data', 'Missing data (MD) – Row summary', and 'Missing data (MD) – Column summary'.

• Geographic distance matrix:  Calculates a geographical (spatial) distance matrix within a set of point coordinates, or between two sets of point coordinates.

• Geographic nearest neighbors:  Calculates nearest neighbors for a given set of points either within the set or with respect to a second set of points.

• CRS transformation for coordinates:  Projects coordinates from two input coordinate columns to new columns based on a different coordinate reference system (CRS).

• CRS transformation for geometries:  Projects an input geometry column to coordinate columns based on a different coordinate reference system (CRS).

• Geographic area of polygons:  Calculates the surface areas for all rows in an input geometry column.

Note: To run the built-in data functions in the web client, an administrator must also have installed the Spotfire Service for Python in your environment. Because some of the calculations can take some time to finish, the administrator might also need to adjust the engine timeout settings for the service.

Pin and search for custom data sources

The experience of working with custom data source extensions, which you develop with the SDK in the Spotfire Developer package, is improved:

• You can now find custom data sources deployed in your environment when you search in the Files and data flyout.

• As an administrator, you can pin custom data sources to the Files and data flyout with the new preference Custom data source locations. You can pin a custom data source directly on the top level of the flyout, or create a folder on the top level to group data sources. By default, custom data sources are available in the Other category.

Access add-ons on the Spotfire Community site from within Spotfire

The Add-ons browser is a new view in the Files and data flyout, where you can browse for visualizations, actions, and demo analyses available on the Spotfire Community site, and open them directly in Spotfire.

Add-ons labeled Data science in the browser are supported by Spotfire and can only be downloaded and configured by users with the Spotfire Data Science license. Data science add-ons include industry-specific visualizations and actions for energy and manufacturing, as well as cross-industry capabilities such as time series and missing data analysis.

To add or save add-ons and demos from the community via the Add-ons browser, you must have a Spotfire Community account.

Action mods enhancements

Significant updates in the action mods framework and API are now available, unlocking more diverse and complex use cases:

Run data functions

It is now possible to add and configure a data function instance (including built-in data functions) from an action in an action mod. This means that, from the same action, visualizations can be automatically created to show the outputs from a data function, and that additional operations can be added before or after the data function call.

Create, configure, and access visualization mods

The API now allows creating, configuring, and accessing visualization mods in the same way as native visualizations.

Icons for individual actions

Each action in an action mod now has a separate icon, which makes it easier to identify the actions in the Actions flyout as well as on action triggers, such as floating buttons and title bar buttons, in visualizations.

Search for individual actions

The search feature in the Actions flyout now also includes individual actions within an action mod.

Embedded resources in action mods

An action mod can now include embedded resources, such as image files or data files, that can be used by the script code and added to the analysis via the API.

Data column, data view, and enum inputs

The range of input types for actions has been extended with more options in the manifest. Running an action with a data column input parameter will expose the user with a searchable point-and-click user interface to select a data column, or a list of data columns from a specified data table. With enum inputs, the user can make a selection from a drop-down list with options defined by the mod developer.

Optional parameters

Input parameters can now be declared as optional, which makes action configuration more flexible and efficient.

Add images to text areas and map charts

Images can now be embedded as resources in an action mod and, through the API, be added to text areas or as image layers in map charts.

Add data as binary columns

An action mod can now add binary data columns to an analysis, either from files embedded as mod resources or generated from script code.

Prompt groups in data connection prompts

You can now use prompt groups when you define prompting for a data connection. Prompts in different groups are independent of each other. That is, your selection in a prompt in one prompt group does not limit the selections available for prompts in a different group.

Support for Parquet files 

Spotfire can now read data from Parquet files, as well as write data to Parquet files. The current implementation primarily supports reading from and writing to Parquet files in local storage. Parquet data types are mapped to supported data types in Spotfire.

Support for private endpoints in Google BigQuery data connections 

With the Google BigQuery connector, you can now access data hosted in private Google Cloud environments. You can configure the private endpoint settings in individual data connections, or you can configure default values to be used for all users in a group (using preferences under Connectors > Google BigQuery in Administration Manager). 

New Spotfire products and licensing

Spotfire 14.5 (and 14.0.8) introduces support for the new Spotfire license model. For more information about the difference between the legacy license model and the new license model see Spotfire licenses and license features in the Spotfire® Server and Environment - Installation and Administration documentation.

The license model to use is determined by your current contract.

For a new installation of Spotfire Server 14.5 or 14.0.8 and later, the default is that the new license model is used. Customers that have contracts with the legacy license model must change the product license version manually using the server CLI command set-config-prop.

Oracle data connector driver included 

You can now use the connector for Oracle without having to install the Oracle driver yourself. The required driver now comes included with Spotfire.

New Oracle functions and data types

The data connector for Oracle now supports using the following Oracle functions for in-database data tables: 

• CONCAT

• LASTDAY

• NEXTDAY

• MONTHS_BETWEEN

• ADD_MONTHS

Additionally, the connector now supports the Oracle data type XMLType. In Spotfire, such columns get the Spotfire data type String.

New supported Citrix version

Citrix Virtual Apps and Desktops 2203 LTSR is now supported for the installed Spotfire client.

Updated driver support for Oracle Essbase connector

The data connector for Oracle Essbase now supports version 21.x of the Essbase Client for Windows.

In-database data access via API

The PersistentDataView API will now work with external data tables.

New license feature for Information Designer

There is a new license feature, Element Administration, that gives users the right to create and edit elements in Information Designer. Elements, such as columns, procedures, and filters, are the building blocks for information links.

With the addition of this license feature, you can create separate groups for users with full permissions to create data sources and information link elements, and users who should only be able to create information link elements.

Added support for .NET 8

Microsoft .NET 8 is now supported for:

• Spotfire Web Player

• Spotfire Automation Services

.NET 8 is the latest LTS release and it was released on November 2023.

Note: This applies to the Spotfire Web Player and the Spotfire Automation Services service when running on Linux.

Note: The support for .NET 6 has now been removed.

Improved multiple selection prompts in data connections

When you open a data connection with a prompt of the type multiple selection, you can now choose to either load the list of values to select from, or type the list of values manually. Entering the values manually can be helpful for scenarios where loading all available values is not optimal for performance, or if you want to select a long list of different values in the prompt. 

As an author, you can configure multiple selection prompts to automatically load all values, or you can let the user choose if they want to enter values manually or load the list of values to select from.

Optional prompts in data connections

You can now configure prompts in data connections to be optional or required. Optional prompts can be skipped without any user input, which gives you greater flexibility when you use prompts in data connections.

By default, new prompts are required, just like before.

Oracle data connector improvements 

The data connector for Oracle has received an overhaul. You can now make use of a wide range of new features when you connect to your Oracle databases: 

Access data from Oracle in the web client

You can now create new data connections in the web client. You can also edit existing connections. This makes it easier to use Oracle data when you author analyses in the web client. 

Note: Some connection authoring capabilities, such as configuring prompts, and writing custom queries, are only available when you use the installed client. For details, see the documentation.

Modernized look 

The Oracle data connector has a new and improved user interface for connecting to your Oracle databases across all Spotfire clients.

Custom properties in connection data sources

When you create a data connection, you can now configure settings in the driver software that the data connector does not have built-in properties for. Custom properties can be useful for tweaking the connection performance, changing the behavior of a connection, or accessing certain data. For example, you can configure pooling settings with the Min Pool Size and Pooling custom properties.

Identity provider authentication

You can now use an identity provider for authentication in data connections to Oracle.

With the Identity provider (OAuth2) authentication method, you can enable a convenient and secure log-in experience for accessing only the data you have permission to access. To learn more, see Single sign-on with an identity provider (OAuth2) for connectors.

Cloudera Impala data connector improvements

The data connector for Cloudera Impala has received an overhaul. You can now make use of a range of new features when you connect to your Cloudera Impala databases:

Access data from Cloudera Impala in the web client

You can now create new data connections in the web client. You can also edit existing connections. This makes it easier to use data from your Cloudera Impala databases when you author analyses in the web client.

Note: Some connection authoring capabilities, such as configuring prompts, and writing custom queries, are only available when you use the installed client. For details, see the documentation.

Modernized look

The data connector for Cloudera Impala has a new and improved user interface for connecting to your databases.

Custom properties in connection data sources

When you create a data connection, you can now configure settings in the driver software that the data connector does not have built-in properties for. Custom properties can be useful for tweaking the connection performance, changing the behavior of a connection, or accessing certain data.

Authentication with an identity provider (OAuth2) for WMS layers

It is now possible to use an identity provider (OAuth2) to log in to a web map services (WMS) server when adding map data to a map chart. This gives you secure access to WMS servers and you can seamlessly browse and add authenticated sublayers to your map charts.

Under Visualizations > Manage external logins, you can see all identity providers used to log in to a WMS server and whose map data is used in visualizations.

Add custom marker shapes to create and share shape collections

You can now upload and use your own marker shapes in the scatter plot and the marker layer of a map chart. This allows you to use industry-specific symbols, such as oil-and-gas or semiconductor symbols, improving the clarity and branding of your analyses.

Create shape collections by uploading images in different formats, including JPG, PNG, and SVG, and share them within teams for reuse across analyses. 

Adjust the anchor position of added marker shapes for optimal placement in visualizations. You can now also change the anchor position for the Spotfire default shapes.

Like the Spotfire default shapes, you can combine the added shapes with other properties and let the data determine the shape, size, and color of the markers in your visualization.

Multiple Y-axis scales in the box plot

Box plots now support multiple Y-axis scales when the visualization is trellised. Each trellis panel can now scale independently and is adapted automatically to the data. To enable this setting, select One scale for each trellis panel in the Y-axis properties.

Using this setting can make it easier to compare distributions across different categories, even if the data analyzed varies significantly in scale.

One user guide for Spotfire

The help content from the installed Spotfire application (previously known as Spotfire Analyst) and the Spotfire web application has now been merged to a single user guide where you can find the help you need regardless of the client you use.

Also, the previously separate user guides for the Spotfire Administration Manager and the Spotfire Qualification tools, as well as the Working with Cubes in Spotfire guide have now been included in the new Spotfire User Guide.

The help is now always opened in your web browser, but you can download the content from the Spotfire documentation site and configure it for offline use. You can also open or download the user guide as a PDF.

Snowflake data connector improvements

The data connector for Snowflake has received an overhaul. You can now make use of a range of new features when you connect to your Snowflake warehouses:

Create and edit Snowflake connections directly in Spotfire

You can now create and edit data connections to Snowflake entirely in Spotfire. It is no longer required that you first configure a DSN for the data source on your computer.

The connector has a new and improved user interface, with built-in controls for a range of connection settings, as well as support for custom data source properties for controlling other settings in the driver software.

Access data from Snowflake in the web client

You can now create new data connections in the web client. You can also edit existing connections. This makes it easier to use data from your Snowflake warehouses when you author analyses in the web client.

Note: Some connection authoring capabilities, such as configuring prompts, and writing custom queries, are only available when you use the installed client. For details, see the documentation.

Custom properties in connection data sources

When you create a data connection, you can now configure settings in the driver software that the data connector does not have built-in properties for. Custom properties can be useful for tweaking the connection performance, changing the behavior of a connection, or accessing certain data.

Identity provider authentication

You can now use an identity provider for authentication in data connections to Snowflake.

With the Identity provider (OAuth2) authentication method, you can enable a convenient and secure log-in experience for accessing only the data you have permission to access. To learn more, see Single sign-on with an identity provider (OAuth2) for connectors.

More properties added to the new visualization properties panel

New configuration and appearance settings are available in the visualization properties panel.

You can now, for example, add error bars to the bar chart, line chart, and scatter plot, add totals to the cross table, add comparison circles to the box plot, configure the size of markers, and sort visualizations by different measures. 

In the KPI chart, more settings are available, such as the option to start each KPI on a new row and to sort the tiles by best or worst.

In the map chart, you can now configure the map type, zoom behavior, and more appearance settings.

This release also includes several improvements to the interaction design, such as undo/redo, formatting, and heuristics to automatically set up visualization axes.

The new visualization properties panel is available in the web client and the installed Spotfire client. Not all visualization properties and functionalities are available yet. The existing properties dialogs can be used side-by-side with this new experience, and they are still the default for configuring visualizations.

API for managing visualization mods

An API has been added for managing visualization mods in the analysis.

This includes the option to install mods from the library, as well as the possibility to add and modify mod instances. This API is available in C# extensions, action mods and IronPython scripts.

Easier to configure a more even routing distribution of web client users over service instances

A new setting has been added to the Spotfire.Dxp.Worker.Host configuration, Health_SimulateRoundRobin. When this setting is enabled, the strained limits are tweaked so that the service instance will always be Strained or Exhausted, which will result in a more even routing distribution, similar to round-robin. This can be useful when multiple copies of the same analysis are opened at the same time.

Switch off revocation checks

It is now possible to switch off revocation checks when verifying certificates.

New menu option to collapse data table filter groups

If you have multiple data tables in an analysis, you can now easily collapse all the data table filter groups by right-clicking in the Filters panel and selecting Collapse all data tables from the menu.

Visualization mods enhancements

A number of improvements are available for visualization mods, including the following:

Defined axis expressions

Visualization mods can now be defined with fixed axis expressions using heuristics specified in the mod manifest. This allows mod developers to ensure that a specific expression, such as Count(), is always used on a designated axis.

Non-aggregating axis expressions

It is now possible to specify that the initial expression on a continuous axis should be non-aggregating.

Undo/redo

Visualization mods now support undo/redo for all configuration changes, which provides a more intuitive experience, consistent with native visualizations.

Browse and save .mod files in web client

You can now browse for, and save, local .mod files also when using the Spotfire web client.

Styling follows the visual theme

The StylingInfo object in the visualization mods API has been extended with more information describing the visual theme used in Spotfire. As a result, zoom sliders and trellis panel headers now follow the current visual theme.

Streaming data updates

The DataView object in the visualization mods API has been extended with an isStreamingUpdate property. This allows the mod to more efficiently adapt to updates caused by streaming data.

Create looping task in Automation Services

A new Automation Services task, ForEach, has been added to allow looping over a list of data.

Create Automation Services task to execute IronPython script

A new Automation Services task, Execute Script, is added to enable the execution of IronPython scripts.

Connection string included in logs for Microsoft SQL Server connections

When you use a Microsoft SQL Server data connection, for TRACE level logging, the sanitized connection string is now written to the log files.

Distribute customized prepared reports

Report developers can distribute a single report as multiple, separate PDFs, where visualizations and key indicators are customized to different target recipients based on selected filter values, bookmarks, and/or document properties. This ensures that only relevant data is shared with the various stakeholders, without any unnecessary information.

This functionality is enabled by the ForEach Automation Services task now available from Automation Services Job Builder in Spotfire Analyst. For example, a report developer can use the ForEach task to loop over a list of bookmarks which filters the data in the report that will be exported. The report can then be sent to different email addresses.

See Emailing reports using a single analysis for more information.

More time granularity and easier repetition patterns for scheduled Automation Service jobs

You can now use common recurrent rules when you schedule an Automation Services job, for example:

• hourly: every X hours

• daily: every X days

• weekly: every X weeks

• monthly: every X months

Recurrent rules simplify event scheduling, improve efficiency, enhance consistency, and provide a structured approach to managing events, ultimately leading to better time management and organization.

Apache Spark SQL data connector improvements

The data connector for Apache Spark SQL has received an overhaul. You can now make use of a range of new features when you connect to your Spark SQL and Databricks databases:

Access data from Spark SQL and Databricks in the web client

You can now create new data connections in the web client. You can also edit existing connections. This makes it easier to use data from your Spark SQL and Databricks databases when you author analyses in the web client.

Note: Some connection authoring capabilities, such as configuring prompts, and writing custom queries, are only available when you use the installed client. For details, see the documentation.

Modernized UI

The data connector for Apache Spark SQL has a new and improved user interface for connecting to your databases.

Custom properties in connection data sources

When you create a data connection, you can now configure settings in the driver software that the data connector does not have built-in properties for. Custom properties can be useful for tweaking the connection performance, changing the behavior of a connection, or accessing certain data.

Identity provider authentication

You can now use an identity provider for authentication in data connections to Spark SQL and Databricks.

With the Identity provider (OAuth2) authentication method, you can enable a convenient log-in experience for connecting to your databases. To learn more, see Single sign-on with an identity provider (OAuth2) for connectors.

Action mods and the Actions flyout

Action mods extend Spotfire with a new type of lightweight reusable action components that can be tailored for specific domains and use cases. Using actions within visual analytics provides extensive options for carrying out tasks and enhancing workflows across all analytic elements, spanning from visualizations to data.

An action mod is a collection of actions (scripts) that are packaged together making them easy to share and reuse. Actions within an action mod can be added to various controls and triggers in visualizations as well as text areas as part of an analytic application, or they can be initiated directly from the new Actions flyout or from the Spotfire library. Triggers can be added to visualizations using the new Action trigger card in the Visualization properties panel, or using drag-and-drop from the Actions flyout.

Action mods follow the same development principles as visualization mods, with external source code control (in e.g. GitHub), modern IDE with syntax highlighting and code completion (e.g. Visual Studio Code) with live debugging in Spotfire. Action mods can be distributed as .mod files and shared through the Spotfire library. The security model is based on a trust mechanism and sandboxed execution.

Similar to IronPython scripts, Action mods use the comprehensive Spotfire API for accessing Spotfire analytic items and services, which allows for implementing actions such as:

• Apply page layouts

• Create and configure visualizations

• Drill down or up in hierarchical data

• Navigate to pages and visualizations

• Run data functions and transformations

• and much more

For information on how to develop action mods, see the Spotfire® Mods website on GitHub.

Copy information about selected library items in Library Administration dialog

In the Library Administration dialog, you can now copy information about the selected library items to the clipboard as a semicolon-separated table. To copy the details about the currently selected items, right-click in the list, and select Copy Selected as Table.

More properties added to the new visualization properties experience (in preview) 

New configuration and appearance settings are available in the preview of the new visualization authoring experience. You can now assign labels to data points, show markers in line and combination charts, configure the projection in map charts, display total bars in waterfall charts, and configure actions on visualizations.

This release also includes several improvements to the interaction design, making the experience more reliable.

Not all visualization properties are available in the new properties panel yet. The existing properties dialogs can be used side-by-side with the new experience, and they are still the default for configuring visualizations. 

Edit column names in Microsoft SQL Server data connections

When you create or edit a Microsoft SQL Server data connection in the Spotfire web client, you can now edit column names in the connection.

Set a custom primary key in Microsoft SQL Server data connections

When you create or edit a Microsoft SQL Server data connection in the Spotfire web client, you can now select and set columns as the custom primary key.

Access data from Microsoft SQL Server in the web client

You can now create new data connections to Microsoft SQL Server in the web client. You can also edit existing connections. This makes it easier to use data from your Microsoft SQL Server databases when you author analyses in the web client.

Note: Some connection authoring capabilities, such as configuring prompts, writing custom queries, and defining primary key columns, are only available when you use the installed client. For details, see the documentation.

New Document properties panel available in all clients

The new Document properties panel enables adding, removing, and editing document properties both in the installed client and the web client. In addition, you now have improved visibility into how document properties affect analyses, including the ability to determine exactly which parts of an analysis are affected by a particular property. It is also much easier to see where a property value is used, with the added convenience of navigating directly to the relevant visualization, and you can even determine if a property triggers a script when changed.

Document properties in Spotfire is a powerful concept which allows you to customize and control various aspects of your analyses using dynamic variables. The properties can be used to control conditional formatting, filter data, control calculations, and trigger scripts based on user interactions. The flexibility and versatility of document properties allows you to tailor your analyses to specific requirements and seamlessly adapt them to changing business needs.

Preview the new visualization properties experience

A preview of the new visualization authoring experience is now available for authors to try out in the web client as well as the installed client. Open it from View > Visualization properties (preview).

The new panel has two different tabs for configuration and appearance settings, and it unifies the experience in the web client and the installed client.

• Easy to use: All properties have one consistent design across all visualization types. The panel only shows properties that are applied to the selected visualizations, but you can add more properties if desired.

• Searchable: You can search for properties and settings to edit or add.

• Efficient: You can configure multiple selected visualizations simultaneously and reuse configurations across visualizations through drag and drop.

• Scalable: The new panel is designed for scale and will allow Spotfire to be extended with more visualization capabilities in the future.

Not all visualization properties are available in the new properties panel yet. The existing properties dialogs can be used side-by-side with the new experience, and they are still the default for configuring visualizations.

Custom panels can respond according to editing or viewing mode

Custom panels can now be shown or hidden depending on whether the application is in editing mode by overriding CustomPanelFactory.SupportsEditingModeOnly.

They can also update their content by checking the new property CustomPanelView.IsEditing.

The Filtering schemes panel shows modified filters

The Filtering schemes panel now shows information about modified filters for all filtering schemes in the analysis. You also have the option to remove specific filter changes.

Modernized UI for Microsoft SQL Server connector

The data connector for Microsoft SQL Server has a new and improved user interface for connecting to your databases.

More metadata shown for TIBCO Data Virtualization external library items

When you use a TIBCO Data Virtualization (TDV) instance as an external library, you can now see metadata information from TDV about the 'Owner' and the available columns for each table.

Manage data table relations from data canvas

In the Spotfire data canvas, the new Relations overview provides a visual graph that vividly illustrates how data tables relate to each other. This new interface simplifies the configuration of data table relations and extends this capability to web authors. The improved error identification makes troubleshooting much easier.

In Spotfire, data table relations shine when working with more than one data table in the analysis. Relations make it possible to carry over marking and filtering between data tables, and foster the creation of details visualizations, empowering users to drill down from one visualization to uncover specifics about selected data in another visualization.

Keyboard shortcuts added in the web client

A number of keyboard shortcuts previously only available in the installed client now work in the web client as well. For example, you can now use keyboard shortcuts to mark all filtered rows (Ctrl+A), filter out marked rows (Ctrl+Shift+M), reset all filters (Ctrl+R), delete all marked rows (Delete), and duplicate the active page (Ctrl+D).

Microsoft SQL Server Analysis Services driver now included in Spotfire

The driver that is required to use the Microsoft SQL Server Analysis Services (SSAS) connector is now included with the Spotfire installation. This means you no longer have to install a separate driver on your computer to access data from SSAS.

Note that the SSAS connector is not available when you run a Spotfire Web Player on Linux, because there is no Linux-compatible driver.

Identity provider authentication in Microsoft SQL Server connections

You can now use an identity provider for authentication in data connections to Microsoft SQL Server.

With the Identity provider (OAuth2) authentication method, you can enable a convenient log-in experience for connecting to your databases. To learn more, see Single sign-on with an identity provider (OAuth2) for connectors.

Custom properties in connection data sources

When you create a data connection, you can now configure settings in the driver software that the data connector does not have built-in properties for. Custom properties can be useful for tweaking the connection performance, changing the behavior of a connection, or accessing certain data.

Custom properties are currently available for the Microsoft SQL Server connector.

Engineering notation available when formatting numbers

Using engineering notation when formatting numbers simplifies the presentation of numeric values in alignment with engineering standards. This feature, which is available under the Scientific format in the column formatting settings, shows the exponent of 10 expressed as a multiple of three, and helps enhancing data comprehension and communication in technical fields.

Add binned columns from the data canvas

Analysts and report developers who are using the installed Spotfire client can now add binned columns to data tables directly from the final data table node in the data canvas. This enhancement adds a quicker access point for grouping a number of more or less continuous values into a smaller number of 'bins'.

Support for IronPython 3.4 scripts

Scripting in Spotfire analyses has been updated to support IronPython 3.4.1, the latest version of IronPython based on Python 3.4, and IronPython 3.4 is now the default option when creating new scripts in Spotfire.
An administrator can decide how older script versions should be handled using the following new preferences:

• Allow authoring of IronPython 2.7 scripts (Default is True)

• Allow IronPython 2.7 scripts to execute (Default is True)

• Allow IronPython 2.0 scripts to execute (Default is False)

To locate analyses containing scripts of versions 2.0 and 2.7 and convert those scripts to 3.4, you can use the find-analysis-script CLI command. It finds all analyses containing scripts in the library, and the resulting report contains information about script language and script language version. See Finding scripts in analyses in the library and Interpreting the find-analysis-scripts results in the Spotfire Server and Environment Installation and Administration manual to learn more.

See What’s New In Python 3.0 to learn more about differences between the 3.x and 2.x versions of Python.

New Filtering schemes panel available in all clients

The new Filtering schemes panel enables adding, editing, and removing filtering schemes both in the installed client and the web client. Now you can also quickly see the number of pages and visualizations limited by a specific filtering scheme and directly jump to a page or visualization.

The filtering schemes functionality is a powerful feature that allows you to save and apply predefined combinations of filters to quickly switch between different data views and enhance and facilitate dynamic data exploration. You can use different filtering schemes across various analysis pages and ensure that specific visualizations remain unaffected by changes in other visualizations.

Support for TLS 1.3

Spotfire clients now support TLS 1.3, provided that this has been enabled on the server, and that the client operating system supports TLS 1.3.

Switch off revocation checks

It is now possible to switch off revocation checks when verifying certificates.

Key-pair authentication method for Snowflake data connections

The data connector for Snowflake now supports using the authentication method key-pair authentication. With key-pair authentication, you use your username, a private key, and sometimes a password to authenticate with Snowflake.

Spotfire username as delegated user in Cloudera Impala data connections

A new data source property, Use Spotfire username as delegated user, is available for data connections to Cloudera Impala. With this property, you can configure a data connection so that the username of the logged in Spotfire user is used as the delegated user (DelegationUID) in the Cloudera Impala system.

New Spotfire products and licensing

Spotfire 14.5 (and 14.0.8) introduces support for the new Spotfire license model. For more information about the difference between the legacy license model and the new license model see Spotfire licenses and license features in the Spotfire® Server and Environment - Installation and Administration documentation.

The license model to use is determined by your current contract.

For a new installation of Spotfire Server 14.5 or 14.0.8 and later, the default is that the new license model is used. Customers that have contracts with the legacy license model must change the product license version manually using the server CLI command set-config-prop.

Load third-party AddIns in separate AssemblyLoadContexts

Third-party extensions can now enable assembly isolation mode when building for .NET, by adding the /loadisolated argument to the Package Builder console when you are building packages. The mode can also be enabled by adding a LoadIsolated="true" attribute to the PackageDescription element in the .pkdesc file.

Contextual menus on filters in text areas

Some of the functionality from the right-click menus that are available in the Filters panel and for filters in the Data in analysis flyout are now enabled also for filters in the text area. This provides easy access to additional filter-specific capabilities in the text area, such as the possibility to reset a filter, or to deselect other values in a hierarchy filter.

Possible to include distribution files in other distribution files

When building a distribution file (.sdn file), you can now include an already built distribution file by specifying this in the distribution description xml file.

Spotfire is back!

Spotfire® is now a stand-alone brand within Cloud Software Group, and this is reflected in a new logotype and new product names.

The following Spotfire products have been rebranded in this release:

• Spotfire Server

• Spotfire Analyst

• Spotfire Deployment Kit

• Spotfire Automation Services

• Spotfire Qualification

• Spotfire Developer

• Spotfire Enterprise Runtime for R (a/k/a TERR)

• Spotfire Enterprise Runtime for R – Server Edition (a/k/a the TERR Service)

• Spotfire Service for R

• Spotfire Service for Python

Run Spotfire Analyst without a server (combined installer with Spotfire Desktop)

You can now run Spotfire Analyst without connecting to a Spotfire Server, by selecting the option 'No server' in the login dialog. If you decide to add a server at a later stage, you can force the login dialog to be shown by searching for 'Spotfire' from the Windows start menu, then selecting the 'Spotfire Analyst (show login dialog)' option, and clicking 'Manage servers' in the login dialog.

The installers for Spotfire Analyst and Spotfire Desktop have been combined. This means that it is easier to switch from one of the sales offerings to another, if your situation changes in the future.

Access data from Google Analytics 4

You can now access data from Google Analytics 4 in Spotfire.

Google Analytics 4 is the current generation of Google Analytics. Google is retiring the previous generation, Universal Analytics, which Spotfire already supports. In this, and later versions of Spotfire, to access your legacy Universal Analytics data, select Connect to > Google Analytics (Universal Analytics).

Fetch size setting for data connections to Oracle

You can now configure the fetch size setting, when you create or edit an Oracle data connection.

Catalog setting for data connections to Databricks

The data connector for Apache Spark SQL has a new setting for specifying what catalog to access data from, when you create or edit a connection to a Databricks system that is set up with unity catalog.

'Reload for each user'-setting available in the data canvas

For an analysis configured to use scheduled updates, the data canvas now allows you to enable or disable the reload of data per data source in each data table.

Scheduled updates save time for consumers by automating data loading for an analysis before the analysis is opened. This reduces the need to wait for new data to load when actually opening the analysis. However, not all data sources are suitable to be preloaded, and now you can easily specify your exceptions from within the data canvas. Read more in Reloading data for each user when using scheduled updates.

Manage column and data table property values from the data canvas

Since version 12.5, analysts and business authors have been able to add new column and data table properties, and edit the default values, from the data tables overview in the new data canvas sidebar.

With this release, analysis authors can also edit the actual column property and data table property values directly from the data canvas, when selecting the final data table node for a data table. This functionality is available both in the installed client and in the web client.

Beyond making this capability available to web authors, the new functionality also makes it more convenient to view and edit the metadata available for your columns and data tables. For example, you can add or edit an optional description of the content, change the content type, or update the link template used for columns that should be interpreted as links.

Configure version history per analysis from the Analyst client

An analyst can enable or disable the version history setting for each analysis in the library from within the Spotfire Analyst client. By only saving the version history for the most important analyses, you can keep the storage need for the library to a minimum.

When an analysis is opened in the installed client, select File > Document Properties, go to the Library tab and modify the Keep older versions of this file when saving check box to change the setting. You need write permissions for the analysis to update the setting.

A system administrator can configure if the version history should be enabled or disabled for all analyses by default. See Switching off library versioning in the Spotfire® Server and Environment - Installation and Administration manual.

Enhanced configuration of the KPI chart 

Several new settings give you more control over the visual layout and formatting of the KPI chart. You can now:

• Start each KPI on a new row to better distinguish them visually.

• Edit the base font style and size in the tiles.

• Set a dynamic tile width relative to the font size to ensure that the content of the tiles is always displayed correctly. 

• Specify a minimum number of tiles per row to preserve the desired layout even when the visualization is resized.

• Set a minimum number of visible tiles to ensure that a certain number of tiles remain visible irrespective of the size of the visualization.

Export tabular visualizations to Microsoft Excel with preserved layout, styling, and formatting

You can now export the table, cross table, graphical table, and summary table visualizations, to an Excel file, preserving their layout, styling, and formatting. This makes it easier to share reports as tabular data, the way they were originally designed in Spotfire.

New Library REST API

The new Library REST API (v2) allows an external application to manage library assets.

The Library REST API supports the following operations:

• list items

• show item details

• download item

• upload item

• delete item

• search items (also with expressions)

The Library REST API also supports operations related to the version history of items.

The Library REST API simplifies promotion and migration operations between Spotfire environments and facilitates automation with CI/CD pipelines.

Easy access to information about data sources in Information Designer

You can now right-click in the Data Sources pane of the Information Designer and select Copy List of Data Sources to see information about all the data sources in your system.

This can be used to locate data sources that use TIBCO-branded DataDirect JDBC drivers, which are no longer supported in Spotfire version 14.0 and forward.

New APIs to customize the KPI chart

The following properties have been added to the KpiChart class:

• MinVisibleTiles - The minimum number of visible tiles in the KPI chart. If necessary, the tiles are scaled down to be visible.

• MinTilesPerRow - The number of tiles to show per row. If necessary, the tiles are scaled down to fit the row.

• NewRowPerKpi - When enabled, the tiles for each KPI start on their own row.

• ShowTitlesForKpis - Only has an effect when NewRowPerKpi is true. Displays the KpiVisualization Title above each KPI.

• AdditionalSpacingBetweenKpis - Only has an effect when NewRowPerKpi is true. Adds additional spacing between KPIs. It is specified in pixels, but is scaled down together with the tiles to comply with MinTilesPerRow or MinVisibleTiles.

• BaseFontMetadata - Allows overriding the base font used in the KPI chart. This is the smallest font used in the KPI chart and all other fonts are derived from this one.

• PreferredRelativeTileWidth - Sets the minimum tile width. It is specified in pixels and relative to the font size. If the font size is increased or decreased, the tile width is adjusted by the same multiple.

The property PreferredTileWidth has been marked as obsolete. Use PreferredRelativeTileWidth instead.

Command timeout for SAP HANA connections

When you create or edit an SAP HANA data connection, you can now adjust the Command timeout.

Control metadata loading for Google BigQuery data connections

In the Administration Manager, there is a new preference setting, Connectors > Google BigQuery > ListAllProjects. With this preference, you can control if you can see and select data from all your projects, or only the selected billing project, when you create or edit a Google BigQuery data connection. By setting ListAllProjects to False, you might be able to reduce the time it takes to load metadata when you open the Views in Connection dialog, especially if you have access to data in many projects.

Connector for TIBCO Data Virtualization supports BOOLEAN

You can now access BOOLEAN type data with the connector for TIBCO Data Virtualization.

Data tables overview in data canvas

If you have an analyst or business author role, and you have access to the Manage Data Tables license feature, you can now view and manage data tables, data tables properties, and column properties from the data canvas, both in the installed client and the web client.

You reach the new overview by opening the data canvas sidebar and clicking on the Data tables header. Click the various tabs in the overview to go to the corresponding section. The data table properties and the column properties views let you view and create new properties, and you can edit default values where applicable.

Save items as favorites in the library

You can now mark individual items (for example, files, folders, information links, data connections, etc.) as favorites in the Spotfire library.

• You can add and remove an item as a favorite by clicking the "star" icon next to the item, in the Files and data flyout or the web view of the library. 

• You can quickly access your favorite items by clicking Favorites in the Files and data flyout.

• The favorite item list is private, only visible to the person that created it.

• The favorites counter, next to the favorites icon, shows the number of users that currently have that item as a favorite.

• The favorites counter is visible to all users that have access to the View favorite counter license feature.

Note: The Spotfire Server administrator can switch off the favorites feature for the entire Spotfire environment, or hide the favorites counter from all users except for library administrators (or another group) using the View favorite counter license feature (under the TIBCO Spotfire Consumer license).

New Markings panel for better overview and management of markings

The new Markings panel enables adding, editing, and removing markings both in the installed client and the web client. In the Markings panel, you can quickly view the number of visualizations that are using or are limited by a specific marking. You can also jump directly to a visualization from the panel.

Markings in Spotfire are visual representations of user-selected data in visualizations, providing a powerful way to interact with, and explore, data. Markings can be used to perform a variety of operations in Spotfire, such as highlighting selected data points, filtering data, and linking multiple visualizations together.

To open the Markings panel, select View > Markings on the menu bar.

Improved usability for data view parameters in external actions

During configuration of a data view parameter, you will now see information about any existing row limits directly in the Configure action flyout. When triggering an action, you will be prevented from running it if the number of rows are not within the specified row limit range. Additionally, an action that works on marked data can be made inactive until some data is marked.

Faster Python data functions

The Python data function execution speed has been significantly improved, leading to more efficient workflows and better productivity.

Beyond generic improvements, run-length encoding (RLE) compression is now available also for Python data functions, which reduces the size of data and therefore reduces network latency.

In the cases where RLE compression is not desired, an administrator can disable this feature via a group preference (PythonServiceUseRunLengthEncoding), using the Administration Manager.

Prompt for username and password in Information Services data sources

In Information Designer, you can now create data sources where end users must log in with their credentials both to access data, and to create a new information link. To achieve this, select the User authentication check box for the data source, and do not input the username and password.

Data canvas sidebar

The new data canvas sidebar allows you to access data tables and data functions more easily than ever before. Quickly switch between a large number of data tables and data function instances in the analysis, with fewer clicks, and navigate through your data with ease.

Open the data canvas and look for the new sidebar on the left-hand side of the screen. Here, all data tables in your analysis, along with any data function instances in use, are displayed. You can collapse or expand the sidebar as needed, to either maximize your working space or to keep the list of data tables available the whole time.

Column description in Data in analysis flyout

You can now add and view column descriptions from the Data in analysis flyout. Descriptions can help you to document the purpose and meaning of data columns, thus making it easier for you and others to understand the analysis and its data.

Simply open the Data in analysis flyout, click on a column and navigate to the Details on selected column view in the expanded flyout. Here you can enter a description for that column.

New Column from marked dialog

In the web client, you can now use the Column from marked functionality to change what column is used on an axis by marking certain data in another visualization. For example, you can create a visualization that is affected by a data table in such a way that when marking certain data in the table, an axis of the new visualization changes to show the value of a specific marked cell in the table.
In the installed client, the existing Column from marked dialog has been given a more modern look and feel.

Improved configuration of external actions

When configuring or running an external action, you will now get more suitable UI controls for each parameter depending on data type. For example, you might see predefined drop-down lists, check boxes, and numeric input controls in addition to text input fields.

This makes it easier for people using the analysis to know what type of input is expected and it reduces the likelihood of issues when an action is run.

Spotfire web client user guide as a PDF

The user guide for the Spotfire web client is now available as a PDF document. 

Document properties values can now be added into Automation Services tasks

You can now use the option Tools > Insert Field in the Automation Services Job Builder to insert the value of a document property into an Automation Services task.

Support for Amazon Redshift ODBC Driver version 2.x 

The data connector for Amazon Redshift now supports using version 2.x of the Amazon Redshift ODBC Driver. 

New functions for Apache Drill data

The data connector for Apache Drill now supports the following functions:

• Quarter

• Week

• DayOfMonth

• DayOfYear

• DayOfWeek

New Automation Services task for executing data functions

A new task, Execute Data Function, has been added to the Automation Services Job Builder. This new task enables running and completing a data function before performing later tasks and also enables chaining executions and completions of multiple data functions in a predetermined sequence in an automated job.

Improved sort order settings from the Data in analysis flyout

If you have access to the Data Panel license feature you can now change the sort order of a column by copying the sort order from another column, when modifying the sort order from the Data in analysis flyout. You can also see a preview of the selected sort order. This functionality is available both in the installed client and in the web client.

View column and data table properties in the data canvas

If you have access to the Manage Data Tables license feature, and you have an analyst or business author role, you can now view all column properties (metadata) available for columns (and, in some cases, also for hierarchies) and data table properties in the data canvas. You can click each graphical node to see the values associated with each node.

Specify key columns for a data table from the data canvas

If you have access to the Manage Data Tables license feature, and you have an analyst or business author role, you can now define key columns for a data table from the data canvas, both in the installed client and the web client.

When key columns are specified, they uniquely identify all rows in the data table and enable functionality for all users of the analysis, such as reapplication of markings, tags or bookmarks when re-opening an analysis. As an author, you can replace specific values in the data table, and the updates are kept when the analysis is reopened.

Specify more data table settings from the data canvas

If you have access to the Manage Data Tables license feature, and you have an analyst or business author role, you can now define more data table settings from the data canvas, both in the installed client and in the web client.

The new Settings popover includes the option to switch data storage settings (linked or embedded in analysis), how to handle filters creation (automatic or manual), as well as additional settings to show/hide the data table in the user interface, enable caching for calculated columns and (in the installed client only) show or skip the column mismatches dialog.

Improved column formatting from the Data in analysis flyout

If you have access to the Data Panel license feature you can now also change the formatting of a column by copying the formatting from another column, when modifying the column formatting from the Data in analysis flyout. This functionality is available both in the installed client and in the web client.

Specification of geocoding in the Data in analysis flyout

If you have access to the Data Panel license feature, and you have an analyst or business author role, you can now easily view and edit geocoding properties from the Data in analysis flyout in both the installed client and the web client.

The expanded Data in analysis flyout now contains a Geocoding section, allowing you to easily specify that a column contains geographic information. This information can be used for positioning data on a map.

Reload all or linked data sources only in the data canvas

If you have access to the Manage Data Tables license feature, and you have an analyst or business author role, you can now reload either all data sources or linked data sources only for a data table in the data canvas.

Log in with an identity provider to TIBCO Data Virtualization

The data connector for TIBCO Data Virtualization now supports using an identity provider (using OAuth2 or OpenID Connect) for authentication. You can use this authentication method in individual data connections, and also when you have set up an external library with the connector.

The following are new features from previous releases, that were not reported in release notes at the time:

API to disable prompts for column matches (since 12.1)

With the API, it is now possible to disable prompts for matching columns when data has been replaced. This can be specified for each data table.

API to set data function categories and icons (since 12.1)

With the API, it is now possible to set categories for data functions, which will affect how they will be presented (icon, keywords) in the f flyout. The API also allows for setting custom icons.

API for position and alignment of legends (since 12.0)

With the API, it is now possible to configure the legend of a visualization to display 'Color by', 'Shape by', and 'Series by' legend items horizontally, above or below the visualizations, aligned left, right or centered.

API to set linear regression fit parameters in data relationships calculations (since 12.0)

With the API, it is now possible for data relationships calculations to configure fit parameters (Slope, Intercept) when using linear regression as the comparison method. The slope indicates the steepness of a line, and the intercept indicates the location where it intersects an axis.

API for zoom interpolation in map chart image layers (since 11.7)

With the API, it is now possible to configure an image in a map chart to keep sharp edges when upscaling the image, to avoid image blurring. This makes it possible to better inspect irregularities within pictures taken by image sensors, such as clusters of defective pixels.

Switch off impersonation for Kerberos

When Kerberos authentication is used, it is now possible to disable impersonation when verifying a certificate.

Access data from Teradata Vantage Cloud Lake

You can now access data from Teradata Vantage Cloud Lake with the data connector for Teradata. 

Configurable labels and descriptions in action input prompts

It is now possible to customize labels and add descriptions in external action prompts, to make it easier for the person running the action to know what type of input is expected.

Optional parameters for actions

To make it easier to configure external actions, it is now possible to skip parameters that you find unnecessary, if they have been defined as optional in the external service.

Data in analysis flyout from data canvas

The data in analysis flyout is now accessible when you are working in the data canvas, thus making it easier to view and edit a column's properties in the context of a selected data table.

Action logging for actions

Usage data for running external actions can now be captured in the user action log. The logs can be analyzed to better understand how the actions are used, and the logged data can also be a support in audits.

Tags in web client

In the web client, it is now possible to attach tags to data rows. This way you can gather data rows exactly as you want, and you will be able to quickly identify the tagged rows in different visualization contexts. For example, you can gather the top hundred values by attaching the same tag to them, or assign 'Good', 'Bad', or 'OK' tags to values.
In the installed client, the existing tags dialogs got a more modern look.

Export data to the library

It is now possible to export data from a Spotfire analysis to the library when working in the web client. The data will be saved as an SBDF file (TIBCO Spotfire Binary Data Format file), which stores the data and metadata. The existing dialog in the installed client has a fresh new look.

Export data to file

In the web client, you can now export data from a visualization or a data table in your analysis to a local file. Depending on the visualization type, or if you export from a data table, you can save the exported data as a text file, a CSV file, an SBDF file (TIBCO Spotfire Binary Data Format file), an STDF file (TIBCO Spotfire Text Data Format), or a Microsoft Excel file. In the installed client, the existing dialog now has a more modern look and feel.

Format dates using the ISO week and year standard

It is now possible to format dates using the ISO-8601 week and year standard. This helps determining how to show date hierarchies in visualizations, and how they are used in calculations. 

The purpose of the ISO-8601 week-based calendar is to provide an unambiguous and well-defined method of representing dates and times, which will avoid misinterpretation of numeric representations of dates and times. This is particularly important when data is transferred between countries with different conventions for writing numeric dates and times.

Copy GUID and library URLs from within an analysis

It is now possible to copy the analysis GUID and library URLs to clipboard from within an open analysis that is saved in the library. Open File > Analysis information to find the GUID and URLs.

Learn which Python packages are available on TIBCO Cloud Spotfire

Spotfire Analyst Help now includes a topic detailing how to create a Python data function that displays the Python packages available on TIBCO Cloud Spotfire.

Improvements to concatenation functions for PostgreSQL-based connectors

The connectors for PostgreSQL, Apache HAWQ, Amazon Redshift, and Greenplum now support using the & operator for concatenating strings. Also, you can now use the CONCAT function for these connectors with more than two arguments, and arguments of types other than string.

Use MAKEUTF8 in connections to Vertica

The connector for Vertica now supports the MAKEUTF8 function.

New Add hierarchy dialog

In the web client, you can now create hierarchies more easily using the new Add hierarchy dialog. 
In the installed client, the existing dialog got a more modern look and feel.

New look for data functions

Data functions can now be shown with a fresh new look, where different, category-based, icons allow faster identification and selection among the many data functions you might have.

Data functions authors can specify an icon for their data functions from a list of predefined categories with an associated icon and keywords, or they can add custom icons.

Access data from Amazon Redshift Serverless

You can now access data from Amazon Redshift Serverless with the connector for Amazon Redshift.

Skip automatic column matches

You can now switch off prompting for column mismatches when replacing data. This is especially useful to avoid interruption of an automated workflow when replacing multiple data tables in sequence.

Existing analyses are not affected. The new setting is available in the data table properties for a specific analysis, as a user level option, or as a group level preference set by an administrator.

Integer input in external actions 

Integer is now a supported input data type for external actions.

Copy coordinates for non-geographical positions

In map charts, it is now possible to get Cartesian coordinates, when the coordinate reference system is set to None.

Updated CustomFileDataSource API

AlwaysLoadOnApplicationThread can now be set via the API for custom file data sources.

Remove items from Recent analyses and Recent data

It is now possible to remove items from the Recent analyses and Recent data sections in the Files and data flyout.

To remove an item, right-click it and select Remove from Recent analyses or Remove from Recent data. Alternatively, in list view, hovering over an item will display a context menu where you can also choose to remove that item.

Access data from Google Analytics 4

You can now access data from Google Analytics 4 in Spotfire.

Google Analytics 4 is the current generation of Google Analytics. Google is retiring the previous generation, Universal Analytics, which Spotfire already supports. In this, and later versions of Spotfire, to access your legacy Universal Analytics data, select Connect to > Google Analytics (Universal Analytics).

Easy access to information about data sources in Information Designer

You can now right-click in the Data Sources pane of the Information Designer and select Copy List of Data Sources to see information about all the data sources in your system.

Command timeout for SAP HANA connections

When you create or edit an SAP HANA data connection, you can now adjust the Command timeout.

Control metadata loading for Google BigQuery data connections

In the Administration Manager, there is a new preference setting, Connectors > Google BigQuery > ListAllProjects. With this preference, you can control if you can see and select data from all your projects, or only the selected billing project, when you create or edit a Google BigQuery data connection. By setting ListAllProjects to False, you might be able to reduce the time it takes to load metadata when you open the Views in Connection dialog, especially if you have access to data in many projects.

Copy coordinates for non-geographical positions

In map charts, it is now possible to get Cartesian coordinates, when the coordinate reference system is set to None.

Support for Amazon Redshift ODBC Driver v2.x

The connector for Amazon Redshift now supports using version 2.x of the Amazon Redshift ODBC Driver. 

Switch off impersonation for Kerberos

When Kerberos authentication is used, it is now possible to disable impersonation when verifying a certificate.

Create packages for both Windows and Linux environments

You can now create packages that can target both Windows and Linux by specifying IntendedPlatform="Universal" and TargetFramework="Any" in the .pkdesc file.

This can be useful for packages that do not contain any .NET code, such as cobranding packages and language packs.

Configurable file system path in Automation Services tasks

Automation Services tasks can now use a new substitution field, exportPath. During execution, the field is replaced by an actual path specified in the service configuration.

Spotfire application identifier in connections to Snowflake

When you access data with the connector for Snowflake, the queries from Spotfire to Snowflake now include an identifier that states that the connection is from a Spotfire application.

Easier to get started with extensions

All C# example extension projects now have a .pkdesc file, that can be used to build packages using the Package Builder console.

Two distribution description .xml files have been included for the C# example extensions, one for Windows and one for Linux.

A new Visual Studio solution has been included that compiles all C# example extension projects.

Two .bat files are included, BuildPackages-windows.bat and BuildPackages-linux.bat. These contain logic to build all valid Windows and Linux packages for the C# example extensions using the included .pkdesc files, as well as building two distribution files containing the packages.

A new command line switch has been added for building distribution files, /ignorespotfirereferences. By using this switch when building a distribution, all references to Spotfire API assemblies are ignored during validation of the built distribution file. This is the recommended way to build distribution files instead of listing Spotfire assemblies in the .pkdesc file as ReferencedFile.

Extensions for Web Player on Linux

It is now possible to create extensions for Web Player that can be deployed to a Web Player running on Linux. Read more in Building packages that work with the Web Player on Linux.

Linear regression with intercept and slope in Data Relationships tool

A new option has been added in the Data Relationships tool to generate fit parameters with intercept and slope information when using linear regression as comparison method.

Apply accessible color schemes to visualizations

You can now apply accessible color schemes for categorical columns with a palette that is compliant with the WCAG 2.1 and conforms with Level AA or higher for the contrast between text and background. There are two variants, one adapted for the light theme and one for the dark theme.

API for scripts in text areas

A new API capability has been added which allows an IronPython script or a C# extension to add new scripts to text areas, as well as to modify or delete existing scripts.

Note: This API is not supported on Linux.

Clickable links in data function descriptions

Clicking on a link in a data function description or a parameter description now opens the target directly in a web browser.

Access data from Amazon Redshift Serverless

You can now access data from Amazon Redshift Serverless with the connector for Amazon Redshift.

Display legend values horizontally

The values of the Color by, Shape by, and Series by legend items can now be displayed in a horizontal legend.

The horizontal legend can be positioned on either the top or the bottom of the visualization. The values inside the horizontal legend can have left, right, or center alignment.

External actions using TIBCO Cloud Integration

The new feature lets you take action in your business systems directly from the visualizations. You can now trigger business processes, update databases, control Internet of Things devices and much more, without having to leave your Spotfire analysis.

This is made possible by integrating with TIBCO Cloud™ Integration, TCI. TCI offers connectivity to a wide range of applications, databases and collaboration platforms, including custom applications reached by standard communication protocols.

With a hybrid cloud architecture, actions can be used in any Spotfire environment, both in the cloud and on premises. This also applies to the systems that actions can integrate with.

Actions are created with no-code user interfaces, both when building the integration apps in TIBCO Cloud Integration and when configuring them in Spotfire.

A security mechanism is provided to protect your sensitive data. Before an action can be applied, it must be trusted, either by the person running the action, or indirectly by the administrator specifying action configurators as trusted signers.

Note: External actions are not supported in the current versions of Spotfire mobile apps (TIBCO Spotfire® for Apple iOS 2.13.0 and TIBCO Spotfire® for Android 1.4.5).

Reduced startup time of Python data functions using pre-initialized background processes

Whether you are running one or multiple Python data functions, you now have a faster overall experience.

Access data from Amazon RDS for Oracle

You can now use the connector for Oracle to access data from Amazon RDS for Oracle.

Page navigation at the top

The page navigation and status bar can now be displayed either above or below the visualizations.

Navigate to linked data table in data canvas

It is now possible to navigate from a linked copy of a data table to its source table in the data canvas.

View version history in the Spotfire library

If version history is enabled on the Spotfire Server, then the File menu now includes the option View version history. You can select this option if you have write access to the currently-working analysis. For TIBCO Cloud™ Spotfire®, all versions are kept at least 30 days. Non-named versions can be deleted after this period. For on-premises or TIBCO Spotfire Cloud Enterprise solutions, the administrator determines the retention policy.

See Reverting to a previous version of a file in the user's guide, or Library version history in the TIBCO Spotfire® Server and Environment manual for more information.

Read connector credentials profiles from files

It is now possible to read connector credentials profiles from files on the computer running the Worker host service. The directory containing the files is defined by the DataAdapterCredentialsFilesDirectory setting in Spotfire.Dxp.Worker.Host.exe.config.

API to change the geometry simplification setting

The threshold for geometry simplification used in feature layers in map charts is now exposed in the API. 

Preferred fonts specified by the administrator

An administrator can now specify a list of preferred fonts to help analysis authors creating analyses based on fonts that are available to all users, for example, a company font.

Amazon Redshift ODBC driver 1.x no longer supported for the Spotfire Connector for Amazon Redshift

Amazon is dropping support for the legacy Amazon Redshift ODBC driver 1.x driver track starting 2026-06-01. Going forward Spotfire will only support the modern Amazon Redshift ODBC driver 2.x driver track for connections using the Spotfire Connector for Amazon Redshift.

Support added for Databricks ODBC Driver

Spotfire now supports using Databricks ODBC Driver for connecting to Databricks. You can still also use Simba Spark ODBC Driver for these connections.

The Snowflake connector, by default, requires that it is possible to connect to Snowflake using SecondaryRoles=ALL.

As of Spotfire 15.0, Spotfire will by default require that a user can connect with SecondaryRoles=ALL. This aligns with Snowflake BCR-1692 and is required for Spotfire to integrate with new Snowflake features including User-Based Access Control (UBAC) and personal databases. See for more information on Snowflake BCR-1692.

This means that an OAuth security integration which is restriced to a single role will not work. Also, programmatic access tokens which are restricted to a single role will not work.

It is possible to fall back to the previous behaviour by setting the preference ForceSecondaryRolesToAll to false.

Note that Spotfire push-compute requires SecondaryRoles=ALL.

Validation of paths in Automation Services ForEach tasks updated

The path to the CSV file used for input to a ForEach task is now validated when the ForEach task is executed, instead of when the Automation Services job starts to run. This makes it possible to use an exported table from an export task as input to the ForEach task.

Support added for Greenplum ODBC driver version 8.0

Spotfire now supports version 8.0 of the Greenplum ODBC driver.

Spotfire Data Science renamed to Spotfire Industry Pro  

Spotfire Industry Pro is the new name for the product offering previously known as Spotfire Data Science. The name has been changed to better reflect the product’s focus on supporting engineers and scientists from data-intensive industries in finding relevant insights and making decisions about their business.

Parallel reload of data

Reload of data now is now done in parallel, in a similar fashion to when data is loaded when first opening a document. This improves performance in cases when data from several sources can be reloaded at once.

• The progress information now more clearly shows what is happening and allows you to copy the separate load times afterwards, for further analysis.

• If there are any prompts for input, these will be shown early, which allows you to focus on other things while the actual reload happens.

Unlike the previously added parallel load, the parallel reload updates also include data functions and data on demand in the parallel part.

In both the load and reload cases, you will now more clearly see which parts of the analysis did not need a refresh (because there were no changes in their inputs). The reload progress will now list them as “cancelled”.

Data functions that execute successfully, but get errors when applying an individual output, will now only fail the part that has errors, instead of the entire data function and all outputs.

The change applies to all explicit reload options of one or more tables in the user interface and API that previously did a synchronous sequential reload. You can switch to the previous synchronous reload behavior by applying the preferences or document setting that controls parallel load.

Allowed TLS versions is no longer SystemDefault

In the configuration of the Automation Services and Web Player services, for the installed client and for the Client Job Sender, the allowed TLS versions default has been changed from SystemDefault to explicitly set the versions to Tls11, Tls12, Tls13. This change was made to avoid problems on certain Windows configurations.

Changed name of Server property in connector for Spotfire Data Streams

In the data connector for Spotfire Data Streams, the Server or stream URL property has been renamed to Server. Connecting directly to a stream URL was only applicable for TIBCO Cloud™ Data Streams, which is no longer available.

Improved discoverability of column properties from the Data menu

In previous releases, configuration of column properties was moved into the Data in analysis flyout. However, the removal of the familiar Data > Column properties option reduced the discoverability of the functionality and made it harder to locate column details when upgrading.

The Data > Column properties menu entry has now been reintroduced as a shortcut to the new workflow. Selecting this option will open the column settings in the Data in analysis flyout.

This change has been done to improve the discoverability and reduce friction when transitioning to the new column management experience, while keeping the modernized workflow intact.

Data in analysis has been moved in the menu bar

The Data in analysis menu item is now in the Data menu instead of in the View menu.

Improved performance for map charts

Updates have been made to improve the performance when you are opening files with map charts containing a large number of geometries and labels.

Telemetry in Spotfire Data Virtualization connections

When you use a Spotfire Data Virtualization data connection, the connection string now includes telemetry (appName=Spotfire), which states that the connection comes from a Spotfire application.

Note: The version of the Spotfire Data Virtualization driver included in this release of Spotfire does not support adding telemetry when connecting to a server. If you manually install a later version of the driver that includes support for telemetry, this fix will add telemetry to the connection string.

New package description attributes for JDBC driver packages

In this version of Spotfire, you can package JDBC drivers for Information Services, and deploy the drivers using the server web administration pages in your web browser. To support this functionality, the following metadata attributes are updated in the PackageDescription element in the Spotfire package description (.pkdesc) specification:

• New value for IntendedClient attribute: "InformationServices"

• New attribute Type, with possible value "JdbcDriver"

• New attribute Capability, with possible value "INFORMATION_SERVICES"

Data Science license no longer required to create and configure Statistica data functions

You can now create and configure a Statistica data function if you have either the Spotfire Data Science or the Spotfire Analytics license. 

Updated display name for license feature for reference elements

The license feature Add and configure reference elements has been renamed to Add and configure enhancing layers in this release. This change has been done to better reflect which type of functionality that the feature might be able to control in the future.

Updated preferences for the visualization properties panel

The preference EnableVisualizationPropertiesPanel has been removed. A new preference, Default to contextual visualization properties panel, has been added, and can be used to specify which visualization properties should be opened by default. See Choose your default visualization properties experience under New Features for more information.

Support added for Databricks ODBC Driver

Spotfire now supports using Databricks ODBC Driver for connecting to Databricks. You can still also use Simba Spark ODBC Driver for these connections.

Validation of paths in Automation Services ForEach tasks updated

The path to the CSV file used for input to a ForEach task is now validated when the ForEach task is executed, instead of when the Automation Services job starts to run. This makes it possible to use an exported table from an export task as input to the ForEach task.

Spotfire Data Science renamed to Spotfire Industry Pro  

Spotfire Industry Pro is the new name for the product offering previously known as Spotfire Data Science. The name has been changed to better reflect the product’s focus on supporting engineers and scientists from data-intensive industries in finding relevant insights and making decisions about their business.

Improved discoverability of column properties from the Data menu

In previous releases, configuration of column properties was moved into the Data in analysis flyout. However, the removal of the familiar Data > Column properties option reduced the discoverability of the functionality and made it harder to locate column details when upgrading.

The Data > Column properties menu entry has now been reintroduced as a shortcut to the new workflow. Selecting this option will open the column settings in the Data in analysis flyout.

This change has been done to improve the discoverability and reduce friction when transitioning to the new column management experience, while keeping the modernized workflow intact.

Allowed TLS versions is no longer SystemDefault

In the configuration of the Automation Services and Web Player services, for the installed client and for the Client Job Sender, the allowed TLS versions default has been changed from SystemDefault to explicitly set the versions to Tls11, Tls12, Tls13. This change was made to avoid problems on certain Windows configurations.

Telemetry in Spotfire Data Virtualization connections

When you use a Spotfire Data Virtualization data connection, the connection string now includes telemetry (appName=Spotfire), which states that the connection comes from a Spotfire application.

Note: The version of the Spotfire Data Virtualization driver included in this release of Spotfire does not support adding telemetry when connecting to a server. If you manually install a later version of the driver that includes support for telemetry, this fix will add telemetry to the connection string.

Data Science license no longer required to create and configure Statistica data functions

You can now create and configure a Statistica data function if you have either the Spotfire Data Science or the Spotfire Analytics license. 

Expanded driver support for data connections to SingleStore

The data connector for MySQL now supports using the official SingleStore ODBC driver and version 8.0.26 MySQL Connector/ODBC driver for connections to SingleStore databases. Also, the connector now prioritizes the Unicode version of drivers over the ANSI version.

Demos in a separate section

Demos are now accessed from their own section of the Files and data flyout instead of from the Add-ons browser.