Question

What best practices do you follow for data validation and audit trails in Power BI solutions?

In my current Power BI project, I need to ensure data accuracy and maintain an audit trail for compliance purposes. I'm looking for best practices to validate data at various stages, such as during data extraction, transformation, and visualization, and strategies for implementing robust audit trails within Power BI solutions to track changes and user activities effectively.

Answer 1

• A multifaceted strategy is required throughout the data lifecycle to enhance the accuracy of the information and provide an audit trail in Power BI solutions. When pulling data from the source systems, utilize system logs to extract the data while also considering using checksum methods or row count to verify the integrity and completeness of the data. Every new set of data has to be processed into the system after making sure all business-required data rules have been adhered to and an accurate and easy-to-follow data lineage exists.
• Employ programs like Power Query to ensure that similar data validation and cleansing processes are performed throughout the transformation stage. Use profiling tools and conditional rules suitable for detecting errors, as well as features for checking mistakes to look for anomalies. For less complicated monitoring, incorporate calculated columns or measures within Power BI that, however, go on to identify and point out any outliers or abnormalities straight into your reports.
• Use the activity logs in Power BI Service to audit user activities such as viewing reports, exporting data, etc. Specifically, record user audits using RLS in PBIX files by restricting user access to data, while user data modification can be recorded through a version control system. In addition, consider integrating advanced auditing and investigative solutions beyond Power BI, including tools such as Azure Monitor. Following these best practices increases the level of assurance that can be placed on the reporting processes while also ensuring that the data remains accurate.