Power BI Data Catalog

What is Power BI Data catalog?

Power BI Data Catalog is a central repository that stores information centrally and helps organize the metadata related to Power BI assets, such as reports, dashboards, and data sources. It allows users to explore different data sources through the data discovery process and helps them understand these sources. It is offered as a fully managed cloud service by Microsoft. It serves as a singular repository for all the users within an organization to contribute data knowledge, build communities of data repositories, and establish a data culture through a data governance structure.

Power BI Data Catalog is a crowdsourcing model that comprises annotations and metadata. Allows everyone, regardless of their role (i.e., developer, data analyst, or other consumers), to discover different data sources, understand their granularity, and consume them for their end reports or analysis.

Note: Power BI data catalog is not a built-in feature in Power BI. There are different external data catalog tools available that can easily integrate with Power BI to provide the features of the data catalog.

Features

A Power BI Data Catalog primarily involves data discovery, understanding data sources, consuming the data sources, and contributing to the data sources.

• Data Discovery: Provides both searching and filtering mechanisms to the users to ensure quick navigation and data discovery of the required data sources. While searching covers a broad range of searches, including user-provided annotations, filtering covers different characteristics, such as data type, object type, tags, etc., to provide the matching data assets and filtered results.
• Data Understanding: Enables users to build a strong understanding of the data contexts, metadata definitions, etc. before consumption
• Data Contribution: You can tag and classify the data into different categories as per the business terms
• Business Glossary: Holistic view of data definitions for various business terms
• Data Lineage coverage: Allows you to trace the data flow across different units and sources/origins to destinations and provides a view on intermediate transformation.
• Data Governance: You can enforce your organization’s policies and access control mechanism across different datasets. You can provision data quality remediation through robust data governance measures.
• Metadata documentation: The business and technical metadata and definitions are documented automatically, thereby eliminating the manual steps and reducing the time and effort.
• Enhanced collaboration: You can easily collaborate and contribute to knowledge due to the centralization of the repository.
• Power BI integration: Data catalog tools support easy and seamless integration with Power BI. It ensures all the Power BI assets can be easily imported to unlock the data catalog features.

In the next section, we will see how you can create a Power BI catalog.

How to Create Power BI data catalog?

In this section, we will go through a couple of examples to understand how you can use the Power BI data catalog.

Example #1

In this example, we will see a data catalog use case in Power BI for data lineage for a financial organization. ABC Corp wants to implement data lineage to monitor data quality issues and understand the data consumption in downstream reporting to produce high-quality reports. To implement the above use cases, follow the steps outlined below:

Step 1: Use the Azure data catalog tool and connect to the Power BI reports or dashboards.

Step 2: Annotate your metadata, add tags with relevant keywords and accurate descriptions to your Power BI reports and dashboards

Step 3: Register your Power BI reports to make it discoverable and searchable.

Step 4: Set up a business glossary such as business definition, description of business rules, data stewardship, and data hierarchy, and tag your power BI reports with these business glossaries.

Step 5: Provide a user or group access to a data catalog and set permissions as per your requirements

Step 6: Run the metadata scanning to capture the data lineage and other definitions. It will make the Power BI reports and dashboards discoverable by other users.

Example #2

In this example, we will see a data catalog use case in Power BI for data governance compliance for a pharmaceutical organization. Bayer AG wants to comply with strict data governance rules and protection requirements by the regulators and monitor the data usage of different Power BI reports to avoid any sensitive information leakage. To implement the above use cases, follow the steps outlined below:

Step 1: Use the Microsoft Purview Service tool for data catalog and connect to the Power BI reports or dashboards.

Step 2: Register the data sources, classify the dataset, and tag them with the correct identifiers to locate any sensitive information

Step 3: Create a comprehensive data catalog mapping the data labels, business glossary, keywords, and data usage trackers across different users

Benefits

The data catalog in Power BI provides multiple benefits, as highlighted below:

Benefits	Description
Easy data discovery	Allows users to quickly discover data sources, both internal and external, with search and filter mechanism ensuring quick navigation and reduction on the elapsed time on data searching and automated documentation.
Enhanced data understanding	Users can gain a better understanding of the data granularity and the context of the data sources, metadata, and relationships.
Data Lineage Efficiency	Provides a holistic view of the data lineage across different data sources
Robust Data Governance	Enables data control over user access, data quality, and usage. This sets a single source of truth and consistent data across the organization.
Improved Collaboration	Allows to establish enhanced collaboration and knowledge sharing across the organization’s users
Enhanced Data Awareness	Enables data literacy of Power BI assets across the organization
Data streamlining	Enhanced streamlined data flow, ensuring reduced data silos across different business units within the organization

Important Things to Note

• As you use different data catalog tools, some of the features and offerings vary across the tools.
• While metadata scanning helps you quickly data catalog all your metadata, it requires a set of Admin REST APIs in Power BI known as the scanner APIs to be set up and configured for integration into Power BI.
• Some of the terms and concepts in the Data catalog may be challenging to understand and hence require extensive user training and continuous communication to ensure there is wide user adoption and data awareness.
• Ensure that you regularly update the metadata and other data information of your Power BI assets to keep your data catalog up-to-date and usable.
• Robust data governance policies and procedures are the need of the hour to streamline your data flow, achieve consistency, and eliminate unauthorized data access.
• If you are using Azure data catalog, ensure that you migrate to Microsoft Purview services or other data catalog tools before August 2025 for uninterrupted experience due to non-IT support from Microsoft.

Frequently Asked Questions (FAQs)

Recommended Articles

This has been a guide to Power BI Data Catalog. Here we explain how to create data catalog in power bi, with features, examples and points to remember. You can learn more from the following articles –

• Power BI Data Source Credentials
• Power BI Dataflows
• Power BI Data Modeling