Daily DAX : Day 132 INFO.CATALOGS

 The INFO.CATALOGS function in Power BI's Data Analysis Expressions (DAX) is part of a set of relatively new "INFO" functions introduced to provide metadata about the semantic model in which it is used. These functions, including INFO.CATALOGS, were made available with the DAX query view updates around December 2023, drawing inspiration from the Dynamic Management Views (DMVs) used in Power BI, Azure Analysis Services, and SQL Server Analysis Services.

What is INFO.CATALOGS?

INFO.CATALOGS is a DAX function that returns a table containing information about the catalogs (databases) available in the current semantic model. In the context of Power BI, a "catalog" typically refers to the database or dataset that the model is based on. This function is particularly useful for introspecting the model's metadata without needing external tools or different query syntaxes like those used with traditional DMVs.

When you execute INFO.CATALOGS, it generates a table with a single column, typically named CATALOG_NAME, which lists the name of the catalog (or database) associated with the current model. In Power BI Desktop, this is usually the name of the dataset you are working with, though in more complex environments (like Analysis Services), it could reflect multiple catalogs if applicable.

Syntax

The function has no parameters:

INFO.CATALOGS()

Return Value

It returns a table with at least one column:

    CATALOG_NAME: A string representing the name of the catalog (database) in the current model.

The exact output depends on the environment, but in Power BI Desktop, it usually returns a single row with the dataset's internal identifier or name.

Use Case

The primary use case for INFO.CATALOGS is model introspection and documentation. It allows you to programmatically retrieve metadata about the dataset you’re working with, which can be valuable in several scenarios:

    Documentation of Models:

        Data analysts or developers can use INFO.CATALOGS to extract the catalog name and include it in documentation or reports about the model. For example, you could run a DAX query like EVALUATE INFO.CATALOGS() in DAX query view to retrieve the catalog name and then copy it into a table or report for reference.

    Troubleshooting and Debugging:

        When working with multiple datasets or in shared environments (e.g., Power BI Service or Analysis Services), knowing the exact catalog name can help confirm which dataset is being queried or troubleshoot connection issues. This is especially useful when the dataset name in the UI doesn’t match the internal catalog name (e.g., a GUID in some cases).

    Dynamic Reporting:

        You can integrate the output of INFO.CATALOGS into a Power BI report to dynamically display the dataset name. For instance, combine it with other INFO functions (like INFO.TABLES or INFO.MEASURES) to create a metadata summary report within Power BI itself.

    Automation and Validation:

        In advanced scenarios, such as automating model deployment or validation scripts, INFO.CATALOGS can be used to verify that the correct dataset is being accessed before running further queries or calculations.

Example in Power BI

To see INFO.CATALOGS in action:

    Open Power BI Desktop.

    Go to the DAX query view (available if enabled in Preview features).

    Enter the following query:

    EVALUATE INFO.CATALOGS()

    Run the query (e.g., press F5).

        You’ll get a table with one row and one column, CATALOG_NAME, showing something like a GUID (e.g., e6b4f3a2-8d9c-4f5b-9e2d-7c8a1b3d5e9f) or the dataset name, depending on how Power BI references it internally.

If you want to use this in a report:

    You could create a calculated table using:

    CatalogInfo = INFO.CATALOGS()

    Then add a visual (like a table or card) to display the CATALOG_NAME.

Practical Example

Imagine you’re maintaining a complex Power BI model shared across a team. You want to create a “Model Info” report page that shows metadata, including the dataset name, table names, and measure details. You could:

    Use INFO.CATALOGS() to get the dataset name.

    Join it with INFO.TABLES() to list all tables and INFO.MEASURES() to list all measures.

    Example DAX query:

    EVALUATE

    SELECTCOLUMNS(

        INFO.CATALOGS(),

        "Dataset Name", [CATALOG_NAME]

    )

    This could be extended with other metadata for a comprehensive overview.

Limitations and Considerations

    Single Catalog in Power BI Desktop: In most Power BI Desktop scenarios, you’ll only get one row because a single .pbix file corresponds to one dataset (catalog). It’s more useful in Analysis Services or multi-database environments.

    GUID vs. Friendly Name: The CATALOG_NAME might return a GUID rather than a user-friendly name, especially in unpublished or service-hosted datasets. You’d need to cross-reference this with external tools (e.g., DAX Studio) if a readable name is required.

    DirectQuery Compatibility: Check compatibility if using DirectQuery mode, as some INFO functions may have limitations depending on the data source.

Conclusion

INFO.CATALOGS is a niche but handy function for metadata retrieval in Power BI. Its primary value lies in simplifying access to catalog information directly within DAX, eliminating the need for external tools or different query languages. While it’s not a function you’ll use daily for data analysis, it’s a powerful ally for model management, documentation, and advanced reporting workflows. As of February 21, 2025, it’s part of an evolving suite of INFO functions that continue to enhance DAX’s capabilities for self-describing models.