This release delivers the SensibleAI Forecast solution.
Enhancements
Source Data Features Revamp
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New Unified Data Management Dashboard: replaced legacy SDF interface with a modern WebDashboard page organized as three connected panels: Data Sources (left), Generators/Data Preview (middle), and Features grid (bottom), streamlining the entire feature data pipeline configuration in one place.
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Enhanced Datasource Editing: supports bulk editing across datasources with guided create, edit, and delete workflows. Users can configure data connection properties, column mapping, and aggregation settings.
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Assignable Source Features: source data features are now assignable, allowing users to target specific source features for assignment alongside standard features.
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Feature Settings Bulk Edit Controls: simplified UI to apply settings across multiple features at once. Supports per-feature overrides for Known In Advance, Data Cleansing Method, Aggregation Method, Hierarchy Groupings, Frequency Override, and more.
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Forecasting Method Configuration: added explicit Forecasting Method selector (None, Lag, Statistical, ML, Smart) at both the datasource and import levels, controlling how feature data extends to the forecast horizon.
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Inline Data Preview & Validation: built-in Data Preview tab shows the first 100 rows of raw data from a selected source with connection metadata and detected frequency.
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Auto-Refresh on Background Jobs: SDF and Feature Package Manager grids automatically refresh when feature data load jobs complete, eliminating manual page refreshes.
Cube Data Integration
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Enables OneStream native cubes to be used as target data sources and supports Consumption Group integration for exporting project results directly back to cubes.
Forecast Analysis
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The Analytics page added under Utilization > Analysis provides visibility into forecast performance metrics and model analytics.
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Embedded web analytics dashboard parameterized by project ID and build info gives each forecast its own analytics context.
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Consolidated analytics hub accessible from the main navigation for monitoring model performance and accuracy metrics.
Feature Forecasting
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Optional Feature Forecasting capability enables future feature values are automatically estimated when source data does not extend through the forecast horizon, helping preserve predictive signals for downstream forecasts within SensibleAI Forecast. Additional details are available in the Feature Forecasting documentation.
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Forecasting Method Configuration introduces configurable forecasting methods (None, Lag, Statistical, Machine Learning, and Smart) at the generator level, allowing users to control how future feature values are extended based on the characteristics of each feature.
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Expanded Feature Generator Support. Feature Forecasting is available across Feature Package Manager, Source Data Features, and Feature Library configuration workflows, providing a consistent forecasting experience regardless of how feature generators are created or managed.
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Intelligent Method Selection. This adds a Smart forecasting option that automatically applies the system-recommended forecasting approach for each supported generator type, simplifying configuration while maintaining flexibility for advanced users.
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Prediction Horizon Support. This automatically extends feature values only when future data is unavailable, ensuring forecasting models continue receiving aligned feature inputs throughout the prediction window without requiring manual data preparation.
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Improved Explainability Integration. Feature Forecasting is fully integrated with Retro Explanations, allowing users to better understand when differences between forecasted and actual feature values contributed to forecast error.
Assign Page
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Safety confirmation dialog box when users attempt to override all target assignments with empty selections. This warns of the destructive action before proceeding.
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Override and Append buttons now activate only when specific rows are selected in the grid, preventing accidental bulk operations on unintended targets.
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Custom Target wizard now respects grid selections, ensuring operations apply only to explicitly selected rows.
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Inline warning messages in the wizard preview step when a destructive override with empty selections is detected.
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Dual-scope validation prevents proceeding with assignments unless either Features or Locations is explicitly selected in the assignment scope.
JSON Enabled Routine Implementation
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Introduces a global setting to designate authorized user groups that can implement routines through JSON-based configurations.
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Includes Target Data Source Validation, Simulator, Consumption Groups, Data Source Updates/Refresh.
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Adds submission documentation outlining required JSON structure, formatting standards, and implementation guidelines.
Hyperscale Storage
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Introduces a new storage strategy that supports increased project creation by allowing users to move projects online or offline, with offline projects remaining inaccessible until restored online.
Hierarchical Column Sets
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Enables configuration of relationships across target data dimensions, with support for applying the setting to both new and existing projects through Global Settings.
AI Project Context
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Adds a new project-level field available during project creation and updates, enabling users to provide contextual information that enhances AI-driven project analysis, recommendations, and agentic development workflows.
AI Activity Center
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Provides a centralized hub for monitoring AI project activity, making it easy to review running tasks, track project progress, and gain visibility into ongoing AI operations across the platform.
Retro Explanations
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This is a new tab in Forecast → Analysis page. It enables users to run Retrospective predictions if data used in a previous prediction has changed, for example, source feature data has changed, historical actuals have been updated, or forecasted features now have actual values. This allows users to answer the question: If we had all of the data we have now when we initially ran this prediction, how much more accurate would we have been?
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Changes in predicted values are explained with Value Changes for any feature with a different value being used in the retrospective prediction, and Impact Changes for features whose value did not change but whose impact on the predicted value did change in the retrospective prediction.
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For every data point in a prediction for which there is now an actual value, the miss is calculated and error is attributed to each feature that was used to generate the forecasted value, allowing users to better understand why a forecasted value missed on any date.
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Attributable Error is calculated for each feature by scaling the effect of the feature on the predicted value by the miss amount. This allows users to see all features the model used and whether they pushed the forecasted value toward or away from the actual value, and by how much, giving a better understanding of why a model missed on any given forecasted value.
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Unexplained Error is any difference between the actual value and the confidence interval band. For example: Actual Value = 500, Forecasted Value = 1000, 95% Confidence Band = 600–1400 → “Unexplained Error” = -100 (500 - 600)
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AI-generated explanations are available on this page to help users better understand the data they are seeing in natural language.
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These calculations depend on Confidence Intervals, so new projects will default to having a 95% confidence band for the top 3 models for each target. This is still configurable, if this functionality is desired on existing projects that don't have Confidence Intervals enabled please go through a manual rebuild and enable them.
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This will only be available on predictions ran after performing the upgrade to 4.3.
Fixed Issues
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Data Update Snapshot Local Time: Instead of using UTC as the standard timing, snapshots are converted to the users local time
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Explanation of Reconciliation Strategies in Hierarchical Forecasting: A full descriptions of each reconciliation strategy is provided right at the implementation source eliminating the need to search through documentation.
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Defaulted Confidence Intervals: Confidence intervals are enabled at all times.
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Dynamic Scaling of Summation Numbers: Easier readability of large numbers throughout the solution.
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Simulator in Utilization: Users can utilize simulator actions in utilization and not just prior to the pipeline.
Upgrade Information
Upgrading to PV9.3.0 SV4.3.0 from any earlier release requires performing an Uninstall Full instead of an Uninstall UI.
Compatibility
Use OneStream Software Platform Version 9.3.0 or later with this version and Xperiflow Version 4.3.0 or later.
Documentation
The Getting Started with Solutions Guide provides general instructions to install and configure OneStream Solutions. It also includes the recommended display settings, package file name information, advice for solution database migration, and considerations for modifications to solutions.
See the Getting Started with Solutions Guide.
Known Issues
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Filling out multiple drop-down boxes within Source Data Upload, Feature Data Upload, or Data Update dialog input forms quickly will fill in with defaulted dimension values instead of persisting the previously selected values. It is recommended to avoid clicking through fields rapidly.
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Within the Pipeline Arena page or the Analysis Forecast page, navigating from the Waterfall or Periodic Explanations views to the Tug Of War view will result in the Tug Of War plot only taking up half the screen. It is recommended to click a dropdown from the model arena table to fix the width of the Tug Of War visual.
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Within the Pipeline Arena page or the Analysis Forecast page, when viewing the Periodic Explanations page, feature names may extend outside of their cell bounds and overlap with the cell values. It is recommended to expand the width of the column by clicking and dragging on the column divider.
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Within the Pipeline Arena page, Analysis Forecast page, Artifacts page on the Runs page of STU, or when inputting parameters for Routine Runs within STU, users may see tooltips over buttons that do not make sense. The first tooltip that is displayed will be correct but subsequent ones may be the same as the first one.
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Within the Pipeline Arena or the Analysis Forecast page, the PolyElasticNet and Cubist Model variants will generate Feature Impact results but will not generate Feature vs. Actual plot data.
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The solution does not block you from making project model build alterations while that project is being copied. It is recommended to avoid making alterations to the project while it is being copied.
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When running model builds that leverage Hierarchical Forecasting with reconciliation, it is possible for targets to disregard the Allow Negative Targets setting and produce forecasts with negative target values.
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When projects are running pipelines or other costly jobs consuming more than 75% of server resources, page rendering speeds may increase by 25%.
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On a project restart, previously configured events may be removed. It is recommended to revisit events and assignments after restarting a project.
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Users are not blocked from running the restart job while a project copy is running. This is not recommended as the projects may end up being in different states. It is recommended to avoid running a restart job (or any other job) while a project is being copied.
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Direct export of SensibleAI Forecast DMF tables that utilize hierarchical forecasting will require manual intervention to populate unused dimension columns with real values.
Contacting Support
Contact OneStream Support by registering at:
Release PV9.3.0 SV4.2.0
This release delivers WCAG 2.1 AA accessibility compliance updates across the SensibleAI Forecast solution.
Compatibility
Use OneStream Software platform version 9.3.0 or later with this version and Xperiflow version 4.2.0 or later.
Upgrade Information
Upgrading to PV9.3.0 SV4.2.0 from any earlier release requires performing an Uninstall Full instead of an Uninstall UI.
Enhancements
WCAG 2.1 AA Compliance
The solution is WCAG 2.1 AA compliant, including but not limited to:
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Keyboard navigation
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Screen readers
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Color contrast
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References the Accessibility Group configured in Xperiflow Administration Tools (XAT) to display BI Viewer graphs in an accessible and compliant manner for users.
Known Issues
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Filling out multiple drop-down boxes within Source Data Upload, Feature Data Upload, or Data Update dialog input forms quickly will fill in with defaulted dimension values instead of persisting the previously selected values. It is recommended to avoid clicking through fields rapidly.
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Within the Pipeline Arena page or the Analysis Forecast page, navigating from the Waterfall or Periodic Explanations views to the Tug Of War view will result in the Tug Of War plot only taking up half the screen. It is recommended to click a dropdown from the model arena table to fix the width of the Tug Of War visual.
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Within the Pipeline Arena page or the Analysis Forecast page, when viewing the Periodic Explanations page, feature names may extend outside of their cell bounds and overlap with the cell values. It is recommended to expand the width of the column by clicking and dragging on the column divider.
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Within the Pipeline Arena page, Analysis Forecast page, Artifacts page on the Runs page of STU, or when inputting parameters for Routine Runs within STU, users may see tooltips over buttons that do not make sense. The first tooltip that is displayed will be correct but subsequent ones may be the same as the first one.
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Within the Pipeline Arena or the Analysis Forecast page, the PolyElasticNet and Cubist Model variants will generate Feature Impact results but will not generate Feature vs. Actual plot data.
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The solution does not block you from making project model build alterations while that project is being copied. It is recommended to avoid making alterations to the project while it is being copied.
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When running model builds that leverage Hierarchical Forecasting with reconciliation, it is possible for targets to disregard the Allow Negative Targets setting and produce forecasts with negative target values.
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When projects are running pipelines or other costly jobs consuming more than 75% of server resources, page rendering speeds may increase by 25%.
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On a project restart, previously configured events may be removed. It is recommended to revisit events and assignments after restarting a project.
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Users are not blocked from running the restart job while a project copy is running. This is not recommended as the projects may end up being in different states. It is recommended to avoid running a restart job (or any other job) while a project is being copied.
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Direct export of SensibleAI Forecast DMF tables that utilize hierarchical forecasting will require manual intervention to populate unused dimension columns with real values.
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Within the Monitor system, if a user deletes a flag, the filters associated with that flag remain and must be manually deleted from the Filters tab.
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When creating a filter in the Monitor system, users can create multiple fallback rules; however, attempting to delete a single fallback rule results in all fallback rules appearing to be deleted.
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In the Monitor system Results page, the model selection displayed per target‑forecastName‑forecastStartDate is accurate; however, the Filter Decision section may reflect an incorrect step in which the model selection was made.
Contacting Support
Contact OneStream Support by registering at:
