Automating the application of sensitivity labels in Power BI using DAX or Power Query is not directly supported, as sensitivity labels are primarily managed through Microsoft Information Protection (MIP) and are configured via the Microsoft Purview Compliance Portal. However, there are alternative approaches to automate the assignment of sensitivity labels based on data classification rules, including using Microsoft Purview and other tools in combination with Power BI. Here are the options and steps you can consider:
1. Automation Using Microsoft Purview (Formerly Microsoft 365 Compliance Center)
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Data Classification Rules: You can configure automatic sensitivity label application using data classification policies in Microsoft Purview. These policies can detect sensitive information based on predefined rules (e.g., credit card numbers, personal data, etc.) and automatically apply sensitivity labels to Power BI content based on the data detected.
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Labeling Policies: In the Purview compliance portal, you can create and configure sensitivity labeling policies that automatically apply labels to Power BI reports and datasets. These labels can be triggered based on content inspection and sensitivity classifications, such as whether the dataset contains sensitive information like personal identifiable information (PII), financial data, etc.
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Auto-Labeling Based on Content: You can set up auto-labeling policies where, for example, a report containing certain types of data (e.g., customer data) is automatically labeled as "Confidential." This process relies on preconfigured content detectors, rather than applying logic via DAX or Power Query.
2. Power BI Dataflow and Power Query Integration
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Manual Label Application Post-Transformation: While Power Query and DAX can't directly apply sensitivity labels, you can leverage Power Query to transform the data and classify it into categories (e.g., based on business rules) that can then guide the manual application of labels. For example, you could categorize data as “High Risk,” “Medium Risk,” or “Low Risk” in Power Query, and then use this information to manually apply the appropriate sensitivity label.
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Power BI Dataflows: If you use Power BI Dataflows to prepare and load data, you can implement classifications and tagging within the transformation process (using Power Query). Although this doesn't automate label application, it can help create clear tags that can later inform the manual labeling process.
3. Using Power BI REST API and Microsoft Graph Security API
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API Integration: While DAX and Power Query can't apply sensitivity labels, you can automate this process by using the Power BI REST API or Microsoft Graph Security API to programmatically apply sensitivity labels to Power BI reports and datasets. By using these APIs, you can trigger label application based on predefined rules from external systems.
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Automation Scripts: You could develop a script or a service that monitors datasets and applies the correct labels based on external logic or classification, triggered by certain conditions or data characteristics.
4. Alternative Approach Using Azure Purview and Power BI Integration
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Azure Purview: You can use Azure Purview, a data governance solution, to classify and manage data assets, including Power BI datasets. Azure Purview offers automated data classification capabilities and integrates with Power BI, allowing labels to be applied based on the metadata and classification rules in Purview.
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Data Insights from Azure Purview: After data classification, Azure Purview can communicate with Power BI to ensure reports containing sensitive information are flagged with the correct sensitivity label, thus providing an automation layer on top of Power BI's reporting capabilities.
