Data Dictionary in Power BI: Create One with INFO.VIEW

One of the most important habits for any data professional is to document your work. In this tutorial, we’ll show you how to quickly create a data dictionary in Power BI Desktop using just a few DAX functions.

A well-documented model helps everyone  from report developers to stakeholders  understand what the data represents, how to interpret it correctly, and where it comes from. Thanks to the new INFO.VIEW DAX functions introduced in October 2024, documenting your model is now faster and easier than ever.

What Is a Data Dictionary?

A data dictionary is essentially a table that captures key information about your model, such as:

• Tables, columns, and measures
• Relationships between tables
• Definitions and calculations
• Key characteristics of your data

Having a single, centralized data dictionary ensures consistency and transparency across your reports.

Why Documentation Matters

There are several reasons to document your Power BI models:

• Ensures everyone is using the same definitions and language
• Helps stakeholders and end users interpret data accurately
• Serves as a single source of truth, particularly for complex or industry-specific metrics

New INFO.VIEW DAX Functions

The INFO.VIEW DAX functions allow you to programmatically extract metadata about your model directly in Power BI Desktop. There are four variations:

• INFO.VIEW.MEASURES  lists all measures with their definitions and DAX code
• INFO.VIEW.TABLES details all tables and their attributes
• INFO.VIEW.COLUMNS  lists columns, data types, and categories
• INFO.VIEW.RELATIONSHIPS  shows how tables are related, including cardinality and filter direction

You can use these functions in new tables within your model to generate the foundation of your data dictionary.

Step-by-Step: Build a Data Dictionary

Documenting Measures

1. Open Power BI Desktop and go to your report.
2. In the model view, select Table Tools > New Table.
3. Enter this formula:

   ModelMeasures = INFO.VIEW.MEASURES()
   

4. Power BI will create a table listing all measures, their DAX expressions, and metadata.

Adding Descriptions

You can enhance your data dictionary by adding descriptions to measures:

• In model view, select a measure.
• In the Properties pane, enter a clear description.
• Refresh your ModelMeasures table to see the updated description appear.

Documenting Tables, Columns, and Relationships

Repeat the process with the other INFO.VIEW functions:

ModelTables = INFO.VIEW.TABLES()
ModelColumns = INFO.VIEW.COLUMNS()
ModelRelationships = INFO.VIEW.RELATIONSHIPS()

Each of these creates a table with relevant metadata.

Combine Metadata Into One Table

For a more advanced approach, you can combine all four tables into a single, dynamic data dictionary using SELECTCOLUMNS and UNION. This allows you to filter and explore all components of your model in one place.

Here’s an outline of how the DAX works:

• Define variables for measures, columns, tables, and relationships using INFO.VIEW functions.
• Use SELECTCOLUMNS to extract only relevant fields.
• Add a Type column to distinguish between components.
• Combine them with UNION into one table called DataDictionary.

This single table can then power a report page with interactive slicers and visuals.

Create a Data Dictionary Report Page

Finally, create a new report page to expose your data dictionary:

• Add table visuals showing names, descriptions, and expressions.
• Add a text slicer to allow users to search by measure name or keyword.
• Optionally, include a slicer to filter by type (Measure, Table, Column, Relationship).

This creates an interactive, dynamic way for users to explore your documentation directly within the report.

Why Use INFO.VIEW Functions?

These new DAX functions make your documentation dynamic. As you add, edit, or remove components in your model, the data dictionary tables automatically update, saving time and reducing errors.

Final Thoughts

The INFO.VIEW functions in Power BI Desktop are a powerful addition for maintaining clear, up-to-date documentation of your models. A well-constructed data dictionary improves trust, transparency, and usability of your reports  all without leaving Power BI.

For more Power BI tutorials and training resources, visit:
Power BI Training at DataBear