Database file

The Save Database File dialog allows you to define where the exported simulation data will be stored. The exported file is created in SQLite format, which is fully supported by Power BI and other Business Intelligence tools.

You can specify the destination folder and file name for the database before starting the export process. Selecting a location that is easy to access from your BI tool is recommended. Once confirmed, @RISK will generate the database file at the chosen location and populate it with the selected inputs, outputs, statistics, and sensitivities.

Database tables and relationships

When you export simulation results using the BI Export feature, @RISK creates a database file that organizes your model’s inputs, outputs, statistics, and sensitivities into a set of related tables. The exported database uses a standard entity–relationship design. Each table represents a specific @RISK element in the simulation, and the tables are linked using identifiers that define how inputs, outputs, statistics, and sensitivities relate to each other.

Model Definition Tables

Model tables contain structural information that describes the @RISK model exported to the database. They serve as the reference layer that supports filtering, labeling, and connecting the data tables during analysis.

  • Inputs: Contains descriptive information for each input variable (name, location, category). All inputs impacting outputs for selected sensitivities will be also included even if no inputs are selected.

  • Outputs: Contains descriptive information for each output variable (name, location, range).

  • Statistics: Defines each statistic and sensitivity included in the export (e.g., mean, percentile, standard deviation).

  • Simulations: Lists of the simulation runs included in the export. Used to distinguish results when more than one simulation or scenario is exported.

  • SimulationInfo: Stores supplemental metadata for a simulation run. Used to provide contextual details of each file.

Data Tables

Data tables store the numerical results generated during the simulation run. These include the iteration-level results for all selected simulations. Data tables form the analytical layer of the export, providing the detailed information needed to build interactive visuals such as histograms, tornado charts, and simulation summaries.

  • InputData: Stores iteration-level values for each selected input variable. Includes data for all simulations.

  • OutputData: Stores iteration-level values for each selected output variable. Includes data for all simulations.

  • InputStatistics: Contains @RISK calculated summary statistics for each input variable.

  • OutputStatistics: Contains @RISK calculated summary statistics for each output variable.

  • OutputSensitivities: Stores sensitivity results linking inputs to outputs. Used to create tornado charts.

 

How to Connect to PowerBI

The SQLite3 Database File (.db) format can be connected directly to Power BI and other Business Intelligence tools using an ODBC (Open Database Connectivity) driver. The driver is installed automatically with @RISK. No additional setup is needed.

The ODBC driver enables Power BI and other Business Intelligence tools to recognize the SQLite3 Database File (.db) format and access the data directly.

To Configure a New Data Source in Power BI follow these steps:

  1. Open Power BI Desktop.

  2. Select Get Data from the Home ribbon.

  3. In the list of data sources, choose ODBC and click Connect.

  4. In the Data Source Name (DSN) field, select SQLite3 Datasource.

  5. Under Advanced Options, define the database connection string using the following format: database=<file path>

  6. Click OK to establish the connection.

Once the connection is created, Power BI displays the available database tables—such as Inputs, Outputs, InputData, and OutputData.

Select the tables you want to import and choose Load to bring the data into Power BI.

Review the example file on how to connect to PowerBI to review to example dashboards learn how to create Histograms and Tornadoes using native charts and Python visuals.

Read our knowledge base article about Automatic relationship detection in PowerBI

Update PowerBI dashboard data

You can update your Power BI dashboard with new simulation results from the same @RISK model or from a different model without rebuilding your visuals.

Refreshing an existing file:

If the database file has been replaced with a new version using the same file name and location, you can update the dashboard by refreshing the dataset in Power BI. Power BI will reload the updated simulation results automatically.

If the new database file has a different name or is stored in a different location, open Transform Data, select Data Source Settings, and use Change Source to update the file path. Power BI will reconnect to the new database and load the updated tables.

When changing the data source, it is important to ensure that the structure and logic of the new @RISK model match the design of your existing Power BI dashboard. Dashboards built using specific Categories, Ranges, inputs, outputs, or naming conventions depend on these elements being present in the new file. If the new model uses different variable names, categories, or ranges—or if certain fields are no longer defined—some visuals may not display correctly or may return errors.