Power BI Integration¶

The following document outlines the process for integrating Power BI Desktop with DataOS.

Prerequisites¶

Power BI Desktop installed on the system(version released after June 15, 2023).

Steps¶

Follow the below steps:

Step 1: Navigate to the Data Product Hub¶

Access the Home Page of DataOS. From there, navigate to the Data Product Hub to explore the various Data Products available within the platform.

Step 2: Browse and select a Data Product¶

Browse the list of Data Products and select a specific Data Product to initiate integration with Power BI. For example, selecting 'Sales360' allows detailed exploration and integration of the Sales360 Data Product.

Step 3: Access integration options¶

Go to the BI Sync option under the Access Options tab. Scroll down to locate the Excel and Power BI section, and click the Download .pbip File button to download the ZIP folder.

Step 4: Download and open the ZIP file¶

Access the downloaded ZIP file on the local system and extract its contents to the specified directory. The extracted folder will contain three files. Ensure all three files remain in the same directory to maintain semantic synchronization of the Data Product.

The folder contains the main components of a Power BI project for syncing the Lens model (here sales360) including folders like the .Report and .SemanticModel. Following is the brief description of each:

public_sales360-table.Report: This folder contains definition.pbir file related to the report definition in Power BI. These files define the visual representation of data, such as tables and charts, without storing actual data. They connect the semantic model and data sources to create the report views.
public-sales360-table.SemanticModel: This folder contains files that define the underlying data model for your Power BI project. The semantic model plays a crucial role in managing how Power BI interacts with data, setting up relationships, hierarchies, and measures.
- definition.bism: This file represents the Business Intelligence Semantic Model (BISM). It defines the structure of your data, including data sources, relationships, tables, and measures for your Lens semantic model. The .bism file holds essential metadata that helps Power BI understand and query the data, forming the core of the data model for report creation and analysis.
- model.bim: Power BI uses the .bim file to generate queries and manage interactions with the dataset. When you build reports or dashboards in Power BI, it references this semantic model to ensure the correct structure is applied to the data.
public-sales-360-table.pbip: This file serves as a Power BI project template or configuration file. Power BI uses files like .pbip or .pbix to encapsulate reports, datasets, and visualizations. The .pbip file ties together the semantic model and report definitions from the other folders, acting as the entry point for working on the project in Power BI Desktop or the Power BI service.

Step 5: Enter credentials¶

Open the public_sales360 file in Power BI, once the file is opened, a popup will appear prompting for the DataOS username and API key.

Step 6: Establish connection¶

Click the connect button. A popup will appear; click OK.

Step 7: View data in Power BI¶

After connecting, users can see tables and views containing dimensions and measures.

Supported data types¶

Category	Data Types	Support Status
Dimension	`time`, `string`, `number`, `boolean`	Supported
Measure	`max`, `min`, `number`, `sum`, `count`, `boolean`, `string`, `time`, `avg`, `count_distinct`	Supported
Measure	`count_distinct_approx`	Not Supported
Rolling Window	-	Not Supported (Power BI doesn’t support)

Important considerations¶

In Power BI, measures typically have an 'm_' prefix to indicate they represent a measure. For example, a measure calculating total revenue might be named m_total_revenue.
The connection is live, meaning any changes to the underlying data will be reflected in Power BI.
When schema changes occur, such as CRUD operations (Create, Read, Update, Delete) on dimensions, measures, or other elements of the semantic model, a re-sync is required. To prevent losing previously created reports after the re-sync, download the model folder from the Data Product Hub, extract the contents, and replace the existing folder with the new one.

Best practices¶

Adhering to best practices ensures that you effectively utilize the Data Product Hub and maintain compatibility with the latest features and updates. Following these guidelines will help optimize workflow, enhance performance, and prevent potential issues.

File handling¶

Ensure that .pbip folders are fully extracted before opening them. Failure to do so may result in missing file errors, as shown below:

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Data retrieval and field selection considerations¶

It is important to select fields from tables that are directly related or logically joined, as the system does not automatically identify relationships between tables through transitive joins. Selecting fields from unrelated tables may result in incorrect or incomplete results.

Troubleshooting¶

Catalog not found¶

If you encounter a 'connection reset' error during Power BI sync as shown below:

DPH

Go to the Home tab in Power BI Desktop.
Click the Refresh button in the Queries section.

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This should resolve the error and restore the sync.

Unknown cluster¶

Whenever you encounter the error 'unknown cluster: ' as shown below, please check if the cluster has been deleted. If it has, redeploy the cluster. After redeploying the cluster, go to Power BI Desktop and click the 'Refresh' button to update the connection.

DPH

Limitations¶

Power BI fails to handle special characters (e.g.,) when generating queries through the synced semantic model, causing errors in visualizations. Thus, it is best practice to address or remove special characters directly in the data itself.
Power BI's Direct Query mode does not support creating custom dimensions and measures or querying the rolling window measure due to the lack of date hierarchy.
DAX functions and Import query mode are not supported.

Governance of model on Power BI¶

Data masking, restrictions, and permissions established by the publisher are automatically enforced for all report viewers, ensuring consistent data security and compliance. The behavior of these data policies, such as masking, may vary based on the use of Power BI Desktop or other interfaces.

When the Lens semantic model is activated via BI Sync on Power BI, authentication and authorization are handled using the DataOS user ID and API key. This ensures that columns redacted by Lens data policies are restricted based on the user's group permissions.

For example, if a user named iamgroot, belonging to the 'Analyst' group, is restricted from viewing the 'Annual Salary' column, this column will not appear in either the Data Product exploration page or in Power BI after synchronization. Power BI requires the DataOS user ID and API key for authentication, ensuring that users can access the full model except for columns restricted by their data policies.

This approach ensures that users only see the data they are authorized to view, maintaining security and compliance.