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Spotfire 14.6 LTS is the new long-term support release, combining the stability enterprises depend on with powerful new capabilities for advanced analytics. This release strengthens Spotfire Data Science with foundational features like Reference Elements, violin plots, and enhanced data functions, unlocking new workflows in manufacturing, energy, and life sciences. It continues to advance the more flexible and intuitive visualization authoring experience, deepens integrations with platforms like Vertica and Dremio, and adds administration enhancements that simplify licensing, automation, and cloud migration. With a new dynamic welcome page and support for the latest enterprise platforms, Spotfire 14.6 makes it easier to explore data, apply advanced analytics, and scale confidently into the future.
As a long-term support release, Spotfire 14.6 also includes all innovations introduced since Spotfire 14.0 LTS (Nov 2023). Customers upgrading from 14.0 gain access to the powerful new capabilities delivered across versions 14.1 to 14.5, including:
The new Spotfire Data Science product for Industrial Analytics which provides domain-specific visualizations and functions such as the well log, 3D surface and line chart, wellbore diagram, time series preprocessing, missing data analysis, geospatial and pattern functions.
New visualization features including custom marker symbols, multiple Y-axis scales in box plots, and enhanced document properties and filters panels.
Automation and customization with Action Mods, looping and scripting in Automation Services, batch editing, personalized report distribution and more flexible scheduling.
Connectivity and administration enhancements such as modernized connectors, OAuth/SSO integration, improved license management, and updated platforms support.
Spotfire 14.6 LTS is the first long-term support release to include Spotfire Data Science, a new Spotfire product introduced in the 14.5 innovation release. Designed for engineers, scientists, and subject matter experts, it combines all the capabilities of Spotfire Analytics with powerful industry visualizations and domain-specific data science functions for deeper insights across energy, manufacturing, life sciences, and other complex industries.
Spotfire 14.6 extends Spotfire Data Science with foundational features such as Reference Elements for thresholds and ranges, Match on Column Names for metadata-driven analytics, and violin plots for richer statistical exploration. These additions make Spotfire Data Science more powerful and flexible, while ensuring scalability for future advanced capabilities.
Spotfire data science
Enrich visualizations with data-driven lines, bands/areas, boxes and markers for additional context, benchmarks, and insights. Place targets, control/spec limits, acceptance ranges, and value windows of interest directly on charts, sourced from expressions or from separate tables, so your visuals stay in sync as rules change. Reference Elements adapt per group/series via split-by (category, color, trellis) and are fully styleable.
What you can do:
Limits & targets (lines): Show spec/control limits or goals as horizontal/vertical lines, per tool/line/segment.
Acceptable ranges (bands/areas): Shade the region between lower/upper bounds to visualize pass/fail windows.
Windows of interest (boxes): Highlight intervals (shifts, outages, maintenance) or value windows.
Benchmark & trend anchors (markers): Pin medians/averages or other aggregates and connect them to reveal drift.
Why it matters:
Metadata-driven dashboards: Bind to auxiliary "tall" rule/target tables (including with Match on Column Names) while plotting "wide" measurement tables.
Scales with your context: Apply automatically per plant, tool, line, lot, or customer segment.
Presentation-ready: Clear labels, and styling for both data exploration and polished analytics applications.
By enriching visualizations with thresholds, ranges, and trends, Reference Elements bridge the gap between raw data and actionable insight while laying a foundation for more advanced analytics workflows in the future.
Spotfire data science
A new column-matching option makes it easy to connect tall parameters/metadata tables to wide measurement tables by matching rows that hold column names (e.g., "Temperature", "Pressure", "Flow") to the corresponding columns in another table.
This is especially useful for Reference Elements scenarios where business rules, targets, or thresholds are defined in auxiliary "tall" tables, while raw measurements come in "wide" tables with many columns.
Key benefits include:
Seamless tall/wide integration: Effortlessly link parameter tables to measurement tables without manual reshaping.
Metadata-driven analysis: Apply control limits, KPI targets, or quality rules defined in separate tables directly on sensor, production, or test data.
Smarter reference layers: Use Reference Elements to display benchmarks stored in metadata tables, keeping visuals automatically aligned as business rules evolve.
Dynamic expressions: Take advantage of constructs like [Axis.Y.Column] to reference the actual column used in a visualization axis, enabling flexible comparisons and calculations.
This makes it far easier to build robust, reusable analytics in industries where thresholds and rules are managed independently of raw data.
Spotfire data science
Box plots can now display violin plots to reveal full probability density distribution (via KDE) around each box to surface skewness, multimodality, and hidden variation not visible with quartiles or medians.
Violin plots are valuable in:
Process engineering to understand variation in yields or defect rates.
Quality analysis to spot distribution shifts in batch performance.
Reservoir engineering to explore performance data beyond summary statistics.
They are available in both vertical and horizontal orientations, with default KDE settings and advanced options to fine-tune scaling, color, and transparency.
Spotfire data science
Usability and flexibility of built-in data functions are enhanced to make it easier to configure, reuse, and apply advanced transformations. Improvements include:
Streamlined parameter handling: Boolean or predefined string parameters now provide selector controls, reducing errors and making setup more intuitive.
Personalized workspace: Built-in data functions can now be pinned or unpinned from the F(x) panel for quicker access.
Improved CRS transformations: Easier coordinate system selection and the ability to pass all or selected columns between input and output tables.
These updates accelerate workflows in manufacturing quality analytics, energy, and natural resources exploration, where built-in data functions and geospatial transformations are core to decision-making.
Spotfire data science Add-on
A specialized scatter plot that overlays 95% and 99.9% control limits to compare rates fairly across different volumes, separating common-cause noise from special-cause outliers. Flag sites with unusually high adverse-event rates in clinical studies, tools or lines with abnormal defect rates in manufacturing, or labs/regions with unexpected positivity rates.
Available as a Spotfire Data Science visualization add-on for Spotfire Data Science 14.5+.
Spotfire data science Add-on
A specialized two-dimensional chart for visualizing data in a circular coordinate system, with support for lines, markers, and areas. Plot azimuth versus inclination or measured depth to reveal wellbore trajectories and drilling directionality, or apply it to other angular domains such as radio frequency detection or particle scattering. Unlike the Spider Chart for categorical comparisons, the Polar Plot is purpose-built for directional analysis.
Available as a Spotfire Data Science visualization add-on for Spotfire Data Science 14.5+.
Spotfire data science Add-on
A connector for loading well log data directly into Spotfire from Log ASCII Standard (LAS) files, widely used in the oil and gas industry. Import well log measurements into Spotfire data tables with control over column data types and custom date/time formats, and capture metadata into column and table properties. Configure the import once in Spotfire Analyst, then save to the library for use across Spotfire, including the web client.
Available as a Spotfire Data Science connector add-on for Spotfire Data Science 14.5+.
Spotfire data science Add-on
A connector for accessing and loading spatial data from ESRI sources into Spotfire. Connect to local file-based GIS Databases (GDB), ArcGIS Online, or ArcGIS Enterprise deployments, then bring the data in-memory to power Spotfire visualizations. Browse and select suitable content items, with secure access managed through OAuth authentication for seamless integration.
Available as a Spotfire Data Science connector add-on for Spotfire Data Science 14.5+.
Spotfire 14.6 LTS introduces new ways to make visualizations clearer, more flexible, and easier to configure, while also strengthening integration with modern data platforms. These enhancements improve dat-to-day analytics for all users and, as always, everything included in Spotfire Analytics is also part of Spotfire Data Science.
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Box plots can now be displayed horizontally, improving readability when working with long category labels or limited vertical space. In analytical workflows—such as comparing yields across production lines, defect rates by machine, or process variation across products—labels often become cramped or truncated in vertical layouts.
The horizontal orientation solves this by optimizing screen space and ensuring labels remain visible. Users can easily switch between vertical and horizontal layouts from the visualization properties or contextual menu. Fully compatible with existing features, horizontal box plots support clearer, more effective communication in both analysis and reporting.
Spotfire analyticsSpotfire data science
The statistics table in box plots is now more flexible, supporting expression-based measures that allow custom calculations—such as yield rates, defect percentages, or process-specific thresholds—directly within the visualization. This removes the need to alter the data table or create extra calculated columns.
The statistics table can also be shown or hidden as needed, giving users full control over the visual layout. Whether for exploration or reporting, this ensures that the most relevant metrics are always visible, meaningful, and aligned with analysis goals.
Spotfire analyticsSpotfire data science
Improved X-axis scale makes dense box plots easier to read by adding scale labels on the X-axis and choosing how categories appear. In workflows like comparing yield across production lines, defect rates by tools, or process variability across products, you can set labels to horizontal (default) or vertical so long or numerous category names don't overlap; making box plots easier to interpret at a glance.
The vertical orientation of scale labels optimizes screen space and ensures labels remain visible. Users can enable labels and their orientation from the visualization properties or the contextual menu. Fully compatible with existing features, including horizontal box plots and trellised views, for cleaner, more effective communication in both analysis and reporting.
Spotfire analyticsSpotfire data science
The long-standing limitation in property controls: 1000-value cap for list boxes, drop-downs, and sliders is removed. Analysts and engineers can now interact with property controls backed by thousands of unique values, without running into silent cutoffs or broken templates. This improvement addresses critical workflows where wide datasets are common, such as:
Manufacturing and Quality Analytics: Selecting predictors variables or dependent measures from pivoted datasets with thousands of columns, without risking hidden value or broken AI/ML templates.
Life Science and R&D: Working with high-dimensional assay data or genomic datasets where column counts routinely exceed 1000.
Energy and Engineering: Interacting with datasets containing extensive sensor arrays or time-series expansions.
Property controls now fetch items dynamically during user interaction, ensuring that all unique values are available while maintaining responsive performance. This change makes Spotfire more robust for modern, high-dimensional data, and removes the need for scripting workarounds often required in the past. By eliminating this hidden constraint, Spotfire delivers a smoother, more reliable experience for organizations working at scale - whether in day-to-day reporting or advanced AI-driven analytics.
Spotfire analyticsSpotfire data science
Ability to edit formatting across multiple columns at once is restored. Now, the Data in Analysis panel includes formatting controls alongside aggregation settings, allowing users to quickly apply consistent formatting across several columns in a single step.
Learn how to work with the new column properties workflow in Spotfire.
Spotfire analyticsSpotfire data science
The new dynamic welcome page keeps users connected with the latest Spotfire resources. Instead of a static start screen, the welcome page now highlights news, events, training, tips, and webinars, with content that updates over time to remain relevant. This makes it easier for users to:
Stay informed about new Spotfire capabilities as they are released.
Access training materials and tips to accelerate learning.
Discover upcoming webinars and events directly from within the application.
The dynamic welcome page ensures that every time users launch Spotfire, they have direct access to the most up-to-date knowledge and resources - helping them get more value from the platform.
Spotfire analyticsSpotfire data science
Spotfire 14.6 LTS continues to advance the new visualization authoring experience, delivering enhancements that make visualization setup more flexible, efficient, and intuitive. This release focuses on improving layout, color management, and customization, while continuing to unify the experience across both the web client and the installed client.
Notable improvements in this release include:
Undockable panel: Move the properties panel around or dock it next to the visualization canvas for a tailored workspace.
Expanded color management: Support for color schemes and simple color rules.
Layer management: Reorder map chart layers for more control and clarity.
Hundreds of under-the-hood improvements and fixes that refine usability, performance, and consistency across visualizations.
The new visualization properties panel makes visualization authoring easier, more efficient, and unifies the experience in the web client and the installed client. It is:
Easy to use: All properties follow a consistent design across all visualization types. The panel only shows properties that are applied to the selected visualizations. Users simply add more properties to enrich visualizations.
Searchable: Users can quickly search to find properties and settings to edit or add.
Efficient: Users can configure multiple selected visualizations simultaneously and reuse configurations across visualizations through drag and drop.
Scalable: The panel is designed for scale and will support the addition of more visualization capabilities in future releases.
The new visualization properties panel is available to all users to explore in both the web client and the installed client. Not all visualizations properties and functionalities are available yet. The classic properties dialog remains available, and is still the default for configuring visualizations, and can be used in parallel while this new experience evolves.
Learn how to work with the new visualization properties panel in Spotfire.
Spotfire analyticsSpotfire data science
The modernized user experience for the Vertica Connector provides a consistent workflow for creating and managing connections across both the desktop and web clients. The connector now supports single sign-on (SSO) with OAuth 2.0 identity providers, enabling secure, personalized access. In addition, the UI exposes new custom connection properties, giving users more control over data source and driver-specific settings to optimize performance.
Spotfire analyticsSpotfire data science
The Dremio connector has been updated to support the latest ODBC driver for Apache Arrow Flight SQL, enhancing performance for large-scale analytics.
Spotfire 14.6 LTS adds new capabilities that simplify administration, enhance automation, and streamline enterprise deployment. These improvements make it easier for IT and administrators to scale Spotfire securely and efficiently across large organizations.
Spotfire enterprise
Timeouts are now configurable at the job level in Automation Services. This allows long-running and short-running jobs to have different execution and wait-time limits, while still maintaining a global default for average jobs. The result is more predictable execution and greater flexibility in managing automated workloads.
Spotfire enterprise
The web administration UI now supports fully configurable tables, giving administrators greater control and efficiency. New capabilities include:
Sorting, resizing, and rearranging columns.
Selecting which columns to display.
Exporting table data to CSV or JSON.
Saving custom table configurations.
These improvements make administration tasks faster, more tailored, and easier to manage at scale.
Spotfire enterprise
New commands (migrate-library and cleanup-migrated-library) make it faster and more reliable to migrate existing Spotfire Libraries to external storage such as Amazon S3, Azure Blob Storage, or Google Cloud Storage. These tools simplify enterprise migrations by providing clearer, more controlled workflows for moving production environments to any supported cloud providers.
Spotfire enterprise
It is easier for customers under the old Spotfire licensing model to adopt the new Spotfire Data Science product. Organizations can now add Spotfire Data Science licenses to their existing subscription without renegotiating their entire contract, just by reaching to their Spotfire Sales contact to add Spotfire Data Science licenses and assigning them directly to user groups via the license management UI. This ensures a smooth transition to Spotfire Data Science while honoring existing agreements.
Spotfire enterprise
Clients registered using register-as-spotfire-community-client command can perform additional actions, such as retrieving dynamic content. Clients registered with earlier Spotfire versions should re-register to take advantage of these enhanced capabilities.
Spotfire enterprise
Spotfire 14.6 adds support for the latest enterprise platforms:
Debian 13 (Trixie)
Windows Server 2025