2026.3 Release Notes

Last updated: July 22, 2026

For a list of release dates and Sisense's end of support schedule, see Sisense Version Release and Support Schedule.

For information about the Sisense gradual rollout process, as well as an explanation of how the versions and release notes relate to content added during the rollout, see Sisense Gradual Rollout Process.

Versions Documented in these Release Notes

• 2026.3.0

• 2026.3.1

if (call.getOperator() == SqlStdOperatorTable.LOG10) { ... }

if (call.getOperator().getName().equalsIgnoreCase("LOG10")) { ... }

new SqlSelect(pos, null, selectList, from, where, groupBy, having,
    windowDecls, orderBy, offset, fetch, hints);
// 12 parameters

new SqlSelect(pos, null, selectList, from, where, groupBy, having,
    windowDecls, null, orderBy, offset, fetch, hints);
//             ^^^^ new 'qualify' parameter (null = not used)
// 13 parameters

@Override
public SqlNode rewriteSingleValueExpr(SqlNode aggCall) { ... }

@Override
public SqlNode rewriteSingleValueExpr(SqlNode aggCall, RelDataType relDataType) { ... }

SqlExtractFunction extractCall = new SqlExtractFunction();

SqlExtractFunction extractCall = new SqlExtractFunction("EXTRACT");

Float pct = ((SqlSampleSpec.SqlTableSampleSpec) spec).getSamplePercentage();

Float pct = ((SqlSampleSpec.SqlTableSampleSpec) spec).sampleRate.floatValue();

with.body.unparse(writer, 0, 0);

SqlWriter.Frame bodyFrame = writer.startList(SqlWriter.FrameTypeEnum.WITH_BODY);
with.body.unparse(writer, 0, 0);
writer.endList(bodyFrame);

2026.3.0 Release Overview

The content below describes the new features, improvements, and bug fixes included in the July 2026, 2026.3.0 release.

What's New

The following table lists the high-level impact (or potential impact, if any) of new features, and how to handle it if upgrading to version 2026.3.0 or newer. Continue reading the Release Notes below the table for a detailed explanation of these features, as well as improvements and fixes.

Compose SDK Version

Compose SDK version used in this Sisense release: 2.30.0

Impersonate User (Log In As User)

Administrators can now start an authenticated session as another user directly from Admin > User Management to reproduce issues and verify per-user configuration exactly as that user sees it.

Key highlights:

• One-click access - Select Log in as user from the Users grid to start an impersonation session. A confirmation modal requires a reason before proceeding.

• Strict role-based authorization - Only System Admins, Admins, and Tenant Admins can initiate impersonation, and only for users with a strictly lower privilege tier. Tenant Admins are restricted to users within their own tenant.

• Supports all authentication types - Local, Active Directory, and SSO (SAML/OIDC) users are all valid targets.

• Full audit trail - Every session start, stop, and action performed during impersonation is recorded in the audit log with the real administrator's identity (impersonatedBy), along with the reason provided.

• Built-in safeguards - Sessions are time-limited (default 30 minutes, max 40), rate-limited per administrator, and capped at 3 concurrent sessions. Password changes, API token creation, and MFA resets are blocked during impersonation.

• Persistent visual indicator - A banner is displayed throughout the session confirming impersonation is active, with a one-click "Return to admin" option.

• Admin opt-out - The feature is enabled by default and can be toggled off under Settings > Security > Authentication Settings > "Enable impersonation for Admins".

Sisense Intelligence Search (Beta)

Sisense Intelligence Search lets you find existing widgets across all of your accessible dashboards using natural language. Instead of navigating dashboard by dashboard or recreating visualizations that already exist, you can describe what you are looking for and get a ranked list of relevant widgets. The search is currently powered by a hybrid search — both vector-based semantic search (so results reflect intent rather than exact keyword matches), not an LLM (no credits consumed) and a lexical search. A future version is planned to be powered only by a vector-based semantic search.

What You Can Do

• Search by intent - type a topic like "revenue" or "financial overview" and get back matching widgets from across dashboards, with widget name, parent dashboard, and data source.

• Act on results - preview a widget, jump to its source dashboard, or pull selected widgets into a new dashboard (create action gated to Designers per Role-Based Access Control (RBAC) ). A future version is planned to include pulling widgets into existing dashboards as well.

• Embedded support - available as an iframe-embeddable surface for embedded customers.

What's New in Beta

This feature was first introduced as Preview in release 2026.2.2. The current Beta milestone addresses post-Preview feedback and hardens the experience:

• Sharper, higher-quality results. Relevance ranking now applies a confidence threshold that hides weak matches rather than padding the list with off-topic results. Exact and strong matches are clearly separated from loosely related "similar" widgets, so you can act on the top of the list instead of sifting through everything.

• A more polished experience. Search now includes clear empty, no-results, and not-indexed states, along with filtering and query chips to refine what you see. Indexing runs invisibly in the background, so search stays available even while your data is being updated.

• Smarter permissions for Viewers. Viewers now see only the actions they are allowed to take — search, preview results, use Find similar, and open dashboards they have read-only access to — with no surprise permission errors. Edit and create actions remain unavailable to Viewers, and gating follows per-dashboard share level rather than system role alone.

How it Works

• Search is powered by a vector database over widget metadata (title, axis labels, metrics, categories, descriptions). No LLM is involved and no credits are consumed.

• When an Admin enables the feature (in Admin > Sisense Intelligence), a full re-index of all published dashboards is triggered automatically. Re-indexing also occurs when a dashboard is republished. A scheduled index refresh keeps data model changes in sync over time.

• Results respect data permissions - users only see widgets they are allowed to view.

• Richer widget metadata (descriptive titles, axis labels) produces better match quality.

Current Limitations

• Compose SDK hook/component is planned for the future, but is not yet included.

• Knowledge-graph integration for usage-based ranking, search across dashboards/data sources/tables, and analytics-tab integration are planned for the future, but are not yet included.

What's Improved

Compose SDK Mode

• CSDK Mode now supports Sisense Intelligence Narratives.

Dashboards

• Several improvements have been made to dashboard semantic search:

  • Unpublished dashboards no longer appear in search results

  • Duplicate entries are removed from search results

  • Overall faster search results

  • New retry mechanism ensures a more complete and up-to-date search index

Filters

• Previously, when the "N/A" value was enabled or disabled in a filter, charts sometimes displayed incorrect results and data was shifted across columns. This has been fixed and "N/A" is correctly positioned on the x-axis and that data remains aligned with its corresponding columns regardless of the filter state.

Infra

• RKE and Kubernetes are upgraded to version 1.36 (latest).

Report Manager

• Reporting Groups (Beta) - The Report Manager can now group recipients who would receive identical report output and generate the report once per group, instead of once per recipient, reducing generation time and resource usage for large recipient lists. A separate copy is still delivered to each recipient; only the generation step is shared.

  Administrators can enable this optimization via the configuration toggle in the Report Manager Global Options > Reporting Groups Enabled (BETA).

  

  Grouping criteria: Recipients are grouped when they share the same data-security rules, dashboard personalization, data model access, user parameters, and language settings.

Sisense Intelligence

• The GET /api/v2/ai/llm/models/providers endpoint has been updated to return a structured catalog of supported LLM providers and their available models, replacing the previous flat array of provider name strings.

  • The endpoint now returns a rich JSON response that includes provider name, display name, and a list of supported models (with name and display name) for each provider.

  • The response accurately reflects the officially supported providers, OpenAI and Azure OpenAI, removing previously listed but unsupported entries.

  • Supported models include GPT-4.1, GPT-4o, GPT-4.1 Mini, and GPT-4o Mini.

  Example response:

  Copy

  {
   "providers": [
    {
     "provider": "openai",
     "name": "OpenAI",
     "models": [
      { "model": "gpt-4.1", "name": "GPT-4.1" },
      { "model": "gpt-4o", "name": "GPT-4o" },
      { "model": "gpt-4.1-mini", "name": "GPT-4.1 Mini" },
      { "model": "gpt-4o-mini", "name": "GPT-4o Mini" }
     ]
    },
    {
     "provider": "azure",
     "name": "Azure OpenAI",
     "models": [
      { "model": "gpt-4.1", "name": "GPT-4.1" },
      { "model": "gpt-4o", "name": "GPT-4o" },
      { "model": "gpt-4.1-mini", "name": "GPT-4.1 Mini" },
      { "model": "gpt-4o-mini", "name": "GPT-4o Mini" }
     ]
    }
   ]
  }

• The LLM providers list on the System Information page is now dynamically fetched via API, ensuring it always reflects the most up-to-date available providers.

• AI models, indexes, and related assets now stay automatically in sync when schema changes are made. Previously, changes to your data model could lead to inconsistent natural language query (NLQ) results or failed enrichment processes.

  With this improvement, the system automatically detects and resolves mismatches caused by schema changes, ensuring that your Sisense Intelligence features, including NLQ, chatbot, and data enrichment, continue to work reliably without manual intervention.

  Impact:

  • More accurate and consistent NLQ results

  • Fewer errors when building or updating AI models

  • No more manual troubleshooting of broken enrichment flows after schema changes

What's Fixed

Add-ons

• JTD - Previously, importing a dashboard built on an ElastiCube into an environment with a Live model of the same name caused the dashboard to incorrectly query the Live model instead of reporting a missing ElastiCube. This led to broken UI elements and non-functional "Jump to Dashboard" (JTD) settings. The system now correctly validates the data source type (Live vs. ElastiCube), ensuring that if the required ElastiCube is not found, an error is displayed rather than querying the wrong data source.

Analytical Engine

• Previously, the "Analytical Engine Settings" option remained visible at the model level even when the global system configuration was set to enforce Analytical Engine only (`AE_ONLY`). This fix ensures that redundant model-level toggles are correctly hidden when the Analytical Engine is globally enforced, providing a consistent user interface across all models.

Build

• Previously, in Linux multi-node environments, stale database farm files were not automatically cleared from the local storage path (/opt/sisense/local_storage) following abnormal pod terminations, such as Out-of-Memory (OOM) events. This could lead to disk space exhaustion on application and query nodes, potentially causing subsequent build failures. A proactive cleanup mechanism has been implemented to identify and remove these orphaned directories during pod startup, ensuring disk space is reclaimed before new extractions begin.

• Previously, dashboards displayed an incorrect "Last Successful Build" timestamp even after an ElastiCube build completed successfully. This occurred due to a processing bottleneck in the message queue. The system now retrieves the build date directly from the database to ensure the timestamp accurately reflects the most recent successful build.

Data Sources & Perspectives

• Previously, when working with a live model, selecting "Change Table" incorrectly opened the "Change Connection" screen instead of the "Edit Table" window. This has been fixed and the "Change Table" action now correctly opens the edit table window with the current table's SQL query pre-loaded, allowing for direct modification.

Exporting Dashboards

• Previously, exporting a dashboard (as a PDF or an image) or republishing it in Shared View did not reflect the current filter state when "Update on Every Change" was disabled; the system would revert to the last published version of the dashboard. This has been fixed and the user's current filter state is correctly captured and applied during export and republishing actions.

Formulas

• Previously, using the `ALL()` function in a formula alongside a date break-by would result in a SQL error (e.g., `types double and timestamp are not equal`) when the AllInMeasuredValueIgnoreFieldInPath setting was enabled. This fix ensures that the query structure remains valid and contiguous when dimensions are excluded by the `ALL()` function, allowing date-based grouping to function correctly.

Report Manager

• Previously, in multi-tenant environments, CSV and Excel report generation failed when the ExportModification plugin was active. This has been fixed and reports retain their custom layout and formatting for tenants without delivery failures.

Services

• Previously, RabbitMQ queues related to the deprecated Acceleration feature (sisense.acceleration.service.delete_dashboard and sisense.acceleration.service.delete_ecm) were not fully decommissioned. This caused messages to accumulate indefinitely in these queues without active consumers, potentially impacting RabbitMQ performance and triggering unnecessary alerts. These queues have now been removed to ensure proper system cleanup and stability.

Sisense Intelligence

• Previously, Administrators and System Administrators encountered an error when attempting to open the assistant on dashboards that were not explicitly shared with them. This fix ensures that privileged roles can access the assistant on any dashboard they have permission to view, regardless of the "Share the assistant" toggle setting, maintaining consistency with general platform permissions. Row-Level Security (RLS) remains fully enforced within the assistant to ensure data exposure remains consistent with standard dashboard access.

• Previously, the "Enable Assistant" toggle was unavailable on dashboards built from data models with names containing a plus (+) character. This was caused by incorrect URL encoding of the data model name, which prevented the system from verifying the assistant's status for that model. This has now been fixed and works as expected.

• Previously, in Sisense Intelligence Search, users with Viewer-only permissions could access the widget editor by clicking "view widget" in search results. The "view widget" action now correctly enforces Role-Based Access Control (RBAC), providing Viewers with a read-only preview or navigating them to the source dashboard instead of opening the editor.

• Previously, the assistant would return a "500 Internal Server Error" when processing queries on extremely large data models (e.g., hundreds of tables and thousands of columns). This occurred because the AI model's response exceeded its output limit while identifying relevant columns, resulting in a truncated response that the system could not parse. This fix increases the allowed response size and improves error handling to ensure the assistant remains stable and provides clearer guidance when dealing with very complex schemas.

• Previously, in on-prem deployments where the `similarity-service` was marked as ready before it could accept traffic, there were connection timeouts (`ETIMEDOUT`) and migration failures in the `ai-integration` service during startup. This has been resolved by adding proper readiness and liveness probes to the Helm charts for the AI-stack components, ensuring services are fully initialized before receiving requests.

• Previously, in Sisense Intelligence Search, performing a search that returned no matches failed to update the UI, leaving the initial landing page visible. This fix introduces a dedicated "no results" state that provides clear feedback and suggestions when no matching widgets or dashboards are found, ensuring that you can distinguish between a search with zero results and a system that is still loading.

• The Narrative button in the assistant UI was previously displayed for on-prem (non-managed) deployments, even though the Narrative feature is not supported in those environments. Clicking the button had no effect. The button is now correctly hidden for on-prem deployments.

Widgets

• Previously, in Compose SDK (CSDK) dashboard mode, when duplicating a widget via the header menu, the widget could not be edited without refreshing the page. This has been fixed and duplicated widgets are synchronized between the React and AngularJS layers, allowing immediate access to the edit toolbar and proper identification of the new widget's server ID.

2026.3.1 Release Overview

Pre-Release

These release notes are being provided in advance of the release, for your preparation and evaluation of the upcoming version. This version will be released for Cloud Availability shortly.

As the content is still in progress, it is recommended that you check back here occasionally for the latest updates.

The content below describes the new features, improvements, and bug fixes included in the August 2026, 2026.3.1 release.

For a list of release dates and Sisense's end of support schedule, see Sisense Version Release and Support Schedule.

For information about the Sisense gradual rollout process, as well as an explanation of how the versions and release notes relate to content added during the rollout, see Sisense Gradual Rollout Process.

What’s New

The following table lists the high-level impact (or potential impact, if any) of new features, and how to handle it if upgrading to version 2026.3.1 or newer. Continue reading the Release Notes below the table for a detailed explanation of these features, as well as improvements and fixes.

Compose SDK Version

Compose SDK version used in this Sisense release: 2.32.0.

Custom AI Context Across the Product (Beta)

Generic AI answers miss the nuances of your data — what "last quarter" means in your fiscal calendar, which joins are correct, or which metrics are canonical. With custom AI context, every AI-generated answer reads like your own team wrote it.

You can now attach custom context, descriptions, and instructions at every level of your analytics stack — data models, tables, columns, dashboards, and widgets — so the assistant answers in your terms, not generic ones.

What's New:

• AI Context at every level — Add custom instructions and semantic context to data models, tables, columns, dashboards, and widgets. The assistant uses this context to generate answers that reflect your business conventions, naming standards, and domain logic.

• Descriptions and tags — Manually author or AI-generate descriptions and metadata tags for tables, columns, dashboards, and widgets to improve discoverability and enrich AI-powered features.

• Scope-aware context resolution — Context can be defined at multiple scopes (model, tenant, user), with the most specific scope always taking priority.

• Cross-product impact — The same context is consumed by the assistant, Narratives, Semantic Enrichment, and NLQ flows, so your business definitions are applied consistently across every AI surface.

Extended Chart Styles

The widget editor's Design panel now covers a significantly broader range of visual styling options, all without writing a single line of code. Dashboard designers and self-service analysts can now achieve polished, on-brand charts directly from the panel, eliminating the need to drop into widget scripts or manually re-apply styles widget by widget. The Design panel is intended to provide no-code customization. However, until now, several everyday styling needs (label formatting, line styles, visual consistency) required a developer and a widget script. This release closes that gap: analysts and dashboard designers can now produce polished, brand-consistent charts independently, without external tools or engineering dependencies.

What's New:

• Line style controls (Line & Area charts) — A new Line Style section lets you choose stroke type (solid, dashed, dotted, and more) and set a custom line thickness, all via intuitive no-code controls.

• Rich value & series label formatting — The Value Label section is extended with:

  • Prefix and suffix text

  • Label rotation (including custom angles)

  • Background color and padding

  • Border color, width, and border radius

  • X/Y offset for precise label positioning

  • Value labels: color, size, and style (normal/italic)

• Pie & Funnel label formatting — The same rich label-formatting options are now available for pie and funnel chart types, with consistent behavior across widget types.

• Legend — Color, size, and style on charts with a legend pane.

MCP Server: Remote Hosting and OAuth 2.1 (Beta)

The Sisense MCP Server is now available as a remote endpoint secured with OAuth 2.1, letting any MCP-compatible AI agent, such as Claude or Cursor, explore your data and build charts under Sisense governance.

The remote server is available for:

• Managed cloud deployments: provided by Sisense as a shared service, hosted and updated by Sisense with no installation or maintenance on your side.

• Self-hosted deployments: provided by Sisense as part of your installation and operated within your own environment.

To connect:

1. Copy the remote MCP endpoint URL for your deployment.

2. Add it as a connection in your MCP client.

3. Sign in with your existing Sisense credentials, including SSO, and approve access.

No identify provider configuration is required.

Agents connect through Sisense rather than directly to your data, so they work against your semantic layer, including your metrics, terms, and relationships, and results reflect your own definitions.

Security and governance:

• Agents connect over OAuth 2.1 with no shared credentials.

• Every request runs as the signed-in user, within that user's permissions, and is fully audited.

Filter Widget (Beta)

Sisense now supports placing interactive filter controls directly on the dashboard as standalone, configurable tiles, removing the dependency on the right-side filter panel.

Dashboard designers can drag filter tiles into any position within the layout as a horizontal bar at the top, in a side column, or inline between content rows, and configure them entirely through the editor without writing any code. Filter tiles work seamlessly in all Sisense embedded deployments (including Compose SDK).

This current phase introduces the list filter type, enabling searchable drop-down controls bound to data dimensions. The filter state persists across page refreshes and respects the dashboard's "Update on every change" setting.

This capability is particularly useful for OEM and embedded analytics customers, where the native filter panel is often hidden or visually incompatible with the host application, by providing a fully integrated, layout-native, filtering experience.

Folder and Asset Organization (Beta)

Sisense now provides hierarchical folder management for dashboards and assets, making it easier to organize, share, and manage your analytics content at scale. Managing dashboard access and ownership previously had to be done one dashboard at a time, which was cumbersome for organizations with many dashboards organized across folders. This update brings folder-level controls for sharing, ownership, and portability, reducing manual effort and empowering teams to collaborate more efficiently without relying on third-party plugins.

What's New:

• Hierarchical Folder Organization — Create folders and subfolders to organize dashboards and other assets in a structured, intuitive hierarchy.

• Bulk Folder Sharing — Share access to an entire folder and all dashboards within it at once, eliminating the need to share each dashboard individually. Sharing can be scoped to specific users or groups.

• Multi-User Folder & Dashboard Ownership — Assign ownership of folders and dashboards to multiple users, enabling any authorized team member to create, move, or manage dashboards within shared folders without requiring a specific user to own the folder.

• Folder Export & Import — Export folders with their complete dashboard contents and restore the full folder structure on import. If a folder already exists in the target environment, you will be prompted to overwrite, consistent with the existing dashboard import experience.

Sankey Chart

Sisense now includes a Sankey chart as a built-in widget, providing analysts and dashboard designers with a native way to visualize how values move, split, and flow between stages or categories, without custom code, plugins, or external tools. Sankey charts are very relevant and useful visualization types for flow narratives. Previously, achieving this in Sisense required custom-coded widgets (BloX / d3-sankey scripts) or exporting data to external tools. This feature keeps you inside the platform for flow-based analysis.

What's New:

• Sankey widget in the chart picker — Add a Sankey chart from the widget editor just like any other out-of-the-box chart type.

• Intuitive field mapping — Map source node, target node, and value (link weight) fields directly in the editor, with optional break-by and color-by for nodes and links.

• Full Design panel support — Customize orientation, node alignment, node width and padding, and link curve, opacity, and minimum width.

• Interactive behaviors — Tooltips, selection/highlight, cross-filtering, and drill-downs work consistently with other Fusion widgets.

• Export & embed — Supports PDF, PNG, and Excel export (including CSDK mode), as well as embed snippets and Pulse integration.

Potential use cases include: Budget and cash-flow allocations, user journey and conversion funnels, source-to-target transfers, supply chain flows, patient pathways, attribution models, and more.

What’s Improved

Analytical Engine

• The Analytical Engine (AE) is now the default dependency generation engine for all Build API workloads. Previously, dependency generation relied on the original translator, which could cause out-of-memory (OOM) errors when processing large dependency graphs. With AE as the default, Build API consumers benefit from improved stability, reduced fallback scenarios, and more scalable dependency evaluation across all customer datasets and dialects.

Calculated Dimensions

• You can now use the SUBSTRING() function inside Calculated Dimension formulas. Previously, it was available only in Custom Columns and Custom Tables (evaluated once at build time).

  Syntax

  SUBSTRING(string, index)

  SUBSTRING(string, index, length)

  Parameters

  • string: The text to extract from. Any field type can be used; non-text values are automatically converted to text.

  • index: The 1-based starting position (position 1 is the first character). Must be a whole number, 1 or greater.

  • length (optional): The number of characters to return. Must be a whole number, 0 or greater. If omitted, the result runs from index to the end of the string.

  See the Dashboard Functions Reference for more information, including examples, behavior, and edge cases.

Data Modeling

• Data designers can now author AI Context, tags, and descriptions for models, tables, and columns directly in the data model UI. These values are saved under the perspective and carried forward through the Publish Semantics, Build, and Publish flows.

Report Manager

• The Report Manager now delivers significantly faster report execution and improved reliability under high-volume workloads. Key improvements include optimized report generation that eliminates redundant processing steps, smarter queue handling for more consistent delivery, and enhanced stability when running large numbers of reports concurrently. These changes reduce report failures and ensure a smoother experience for organizations with heavy reporting needs.

Sisense Intelligence

• The Query Built tool card in the assistant chat now displays a visual chipset breakdown as the default view, along with a separate dashboard filters breakdown. You can toggle to the full JSON representation for advanced inspection.

• Sisense now supports Bring Your Own LLM (BYO LLM) with selected AWS Bedrock models, extending provider support beyond OpenAI and Azure. You can now connect your own Anthropic models hosted on Amazon Bedrock, providing greater flexibility in choosing the LLM provider that best fits your needs.

• Error handling and feedback in the AI administration interface (Admin > Sisense Intelligence) has been improved. Previously, connection failures for custom Vector Databases (VDB) or LLM providers often resulted in generic error indicators or full-page blocks without specific details.

  With this update, the system now provides detailed, actionable inline error messages directly within the provider cards and configuration pages. These messages specify the cause of the connection failure—such as invalid credentials, unreachable hosts, or malformed connection strings—allowing for faster troubleshooting. Additionally, the interface now supports graceful degradation, ensuring that secondary request failures no longer block access to the entire page, keeping other administrative actions available.

Snowflake Connection Setup - Improved UI

• The Snowflake connector setup in the Add Data wizard has been redesigned to make creating a connection faster and less error-prone. Previously, connecting required manually composing a JDBC connection string – a common source of errors. The new guided form shows only the required fields up front, using standard Snowflake terminology:

  • Address – Enter your Snowflake Account Identifier directly – no connection string needed.

  • Authentication – Select an authentication method: Private key (PEM) (default), Private key file path, or Password. Private keys can now be added by dragging and dropping the key file, instead of opening it and copy-pasting its contents.

  • Additional Configuration – Role, Warehouse, Database, and Schema are now optional instead of mandatory, and are collapsed under Additional Configuration together with the Use Dynamic Schema option and connection description. When left empty, your Snowflake defaults (such as the default warehouse) are used.

  • Clearer connection testing – Test Connection now surfaces the specific problem inline, with a copyable error code – for example, incorrect username or password, an invalid role, a warehouse that doesn't exist, or an encrypted private key provided without its passphrase – instead of a generic failure later in the process.

  • DBA request template – If you don't have the required permissions or credentials, click Need help from your DBA? to generate a ready-to-send message for your data administrator that includes the Sisense IP addresses to allowlist, the required access grants, and the RSA public key registration command.

  • Documentation link – Click Open documentation to go directly to the Snowflake connector documentation.

  If you prefer to connect using a JDBC connection string, click Use JDBC connection string instead to switch to the JDBC form, which supports an optional private key and key passphrase. You can switch back to the guided form at any time.

  Note:

  While new Snowflake connections will use this new form, existing connections will continue to use the previous form.

What’s Fixed

APIs

• Previously, the GET /builds/{buildId} API endpoint incorrectly returned a `400 Bad Request` error instead of a `404 Not Found` error when a build ID no longer existed in the system. This fix ensures the API correctly identifies missing resources, allowing for more accurate error handling and alerting in automated workflows.

Build

• Previously, ElastiCube build failure could result in the build status being incorrectly displayed as "Running" in the UI, accompanied by a "cubeIsUnreachable" error. This occurred due to a race condition where metadata was not updated if cleanup tasks hung after a failure. This fix ensures that the build status is correctly updated to "Failed" immediately upon a workplan failure, allowing users to trigger new builds without manual intervention.

Dashboards

• Previously, ElastiCubes could become stuck in a "STOPPING" state, preventing dashboards from loading and resulting in errors such as "ElastiCube not found on LocalHost." This occurred due to a race condition between the Stop When Idle feature and other lifecycle events, such as post-build pod spin-ups or system upgrades. This fix ensures these operations are properly synchronized and includes a recovery mechanism to automatically clear stuck states, ensuring consistent dashboard availability.

Data Models

• Previously, the Data page would fail to load and display zero data models following bulk concurrent user deletions. This occurred due to a race condition that could leave orphaned share entries in the system. This fix implements guards to prevent these orphaned entries and includes a self-healing mechanism to automatically resolve any existing instances.

• Previously, AI-driven context and suggestions were not displayed for Live Columns. This fix ensures that the context field is correctly populated and visible within the Live Column interface, providing users with the expected AI insights when working with Live models.

Explanations

• Previously, in the Explanations wizard, the "Explore other fields" button was visible to Viewer users who lacked the necessary data source permissions. Clicking the button resulted in a console error and failed to open the field selection modal. The button is now correctly hidden for users without "Can Use" or higher permissions to the underlying data model.

Export to PDF

• Accordion add-on: Previously, exporting to PDF from a Pivot table drilled within an Accordion widget embedded inside a Blox or Indicator widget exported all data instead of the filtered/drilled data. This has now been fixed and Export to PDF saves filtered data as it is in the Pivot table and even in the downloading preview.

Filters

• Previously, scrolling within an individual filter using a mouse wheel or touchpad was not possible when the main Filters Panel was already scrolled to the very top or bottom. This fix ensures that scroll events are correctly captured by the specific filter component, allowing for smooth navigation through filter values regardless of the main panel's scroll position.

Formulas

• Previously, formulas saved as favorites ("starred" formulas) while the Shared Formulas feature was disabled were not automatically converted to shared formulas upon enabling the feature. This fix ensures that all previously starred formulas are correctly migrated, preserved, and displayed within the formula editor as intended.

Functions

• Previously, in a Pivot widget, using the NOW() function in a formula alongside a multi-pass SUM() measure caused a query error. This occurred because certain complex grand-total calculations incorrectly triggered a fallback to the original translator, which did not support the NOW() function's syntax. This fix ensures these queries are processed correctly by the Analytical Engine.

Multitenancy

• Previously, in multi-tenant environments, a System Admin accessing a dashboard from a different tenant and selecting Open Data Source could cause data model corruption. This occurred because the system incorrectly synchronized metadata across tenants, potentially changing the model type, altering ownership, or removing the dataset from the UI. This fix ensures proper tenant validation to maintain data model integrity when accessed by administrators across different tenant contexts.

Narrative

• Previously, AI-generated narratives sometimes incorrectly modified the casing of data values and column names (e.g., converting "USD" to "Usd"). The system now preserves the original casing from the data source, ensuring technical identifiers and standardized codes remain consistent and professional.

• Previously, the AI-generated narrative incorrectly used sales-oriented terminology (such as "market engagement" or "high-value sales") regardless of the actual data domain. The narrative now correctly incorporates the data model's schema and column context to ensure the generated analysis uses domain-appropriate language, such as "payable volumes" or "vendor invoices" for Accounts Payable data.

Outer Joins

• Previously, widgets would fail with a "field not found" error when a dashboard filter was applied to a column in a left-joined table, but that column was not explicitly included in the widget's data panels. This occurred specifically when the tables were joined using a composite key (multiple columns). This fix ensures that filters on non-key columns are correctly resolved and applied through the join path regardless of whether the column is displayed in the widget.

Pivot Tables

• Previously, in Pivot widgets, enabling a formula using the `Rank` function caused rows with null (empty) values to be removed from the widget entirely. This occurred because the system automatically filtered out rows that could not be ranked. With this fix, rows with null values are no longer dropped; instead, they remain visible in the pivot with a blank rank.

Report Manager

• Previously, Report Manager PDF exports would fail or hang indefinitely for specific users if their theme reference was invalid or broken. The system now automatically falls back to the default theme in such cases, and the export process will fail quickly with a clear error message if themes or fonts cannot be loaded, rather than waiting for a full timeout.

Single Sign On (SSO)

• Previously, the Single Sign-On (SSO) settings page in the Admin UI appeared blank or failed to display configuration values for Tenant Admins. This occurred because the system incorrectly returned a server error when a Tenant Admin attempted to access license information, causing the page to crash. This fix ensures that the SSO settings page now renders correctly, allowing Tenant Admins to view and manage their SSO configurations as expected.

Sisense Intelligence

• Previously, toggling the dashboard filters after executing a query would retroactively alter an already-built Build Query card. The Build Query card now remains static, reflecting the dashboard-filters toggle state at the moment of execution. An explanatory message now indicates whether dashboard filters were applied at the time of the query execution.

• Previously, the assistant failed to generate queries for fields with names ending in parenthetical suffixes, such as "Handle time (s)" or "Revenue (USD)". This occurred because the system incorrectly stripped these suffixes, treating them as display metadata rather than part of the actual field name. The assistant now correctly identifies and preserves these suffixes, ensuring accurate query generation for all field types.

• Previously, the semantic search index was cleared and left empty if a full reindex was triggered when no published dashboards were available. Additionally, publishing a dashboard that was not shared would fail to index, preventing it from appearing in semantic search results. Both of these issues have now been fixed and work as expected.

• Previously, the Sisense Intelligence Feature Management admin page would fail to load if the system encountered an error retrieving the list of AI providers. The page is now more resilient; if the provider list cannot be loaded, an inline error message will appear specifically in that section, while all other Feature Management controls remain accessible and interactive.

Widgets

• Previously, widgets failed to load and displayed "N/A" when a user's timezone was set using a three-letter abbreviation (e.g., MST, EST, HST) instead of a full IANA timezone ID (e.g., America/Phoenix). The connector now correctly recognizes and maps these common abbreviations, ensuring data is extracted successfully regardless of the timezone format provided in the connection string.

• Previously, Table widgets with pagination enabled would ignore the widgetQueryLimit setting if it was set to a value greater than 25. This enabled users to navigate through additional pages and access the entire dataset beyond the configured limit. The limit is now correctly enforced across all pages.