Intermediate Level


1. Explain the concept of incremental data refresh in Power BI and its benefits?

Incremental data refresh in Power BI allows you to refresh only the new or modified data since
the last refresh, rather than refreshing the entire dataset. This improves performance and reduces
resource consumption, particularly for large datasets.

2. How can you implement advanced analytics and machine learning in Power BI?

Advanced analytics and machine learning can be implemented in Power BI using techniques such
as integrating R or Python scripts, leveraging Azure Machine Learning services, or using custom AI
visuals.

3. What is the VertiPaq engine, and how does it optimize data storage and retrieval in Power BI

The VertiPaq engine is the in-memory data storage and query processing engine used by Power
BI. It optimizes data storage through columnar compression and enables fast query performance by
leveraging in-memory processing and parallelism.

4. Explain the concept of composite models in Power BI and when they should be used?

Composite models in Power BI allow you to combine both import and DirectQuery data sources
within the same model. They should be used when you need to combine large datasets with real-time or semi-real-time data sources, maintaining optimal performance and flexibility.

5. What are the considerations for optimizing data refresh performance in Power BI Service?

Optimizing data refresh performance in Power BI Service involves considerations such as
scheduling refresh during off-peak hours, optimizing data source queries, reducing unnecessary data
transformations, and leveraging incremental refresh where possible.

6. How can you implement advanced data visualization techniques in Power BI?

Advanced data visualization techniques in Power BI include using custom visuals, incorporating
interactive features like bookmarks and drill-through, implementing complex animations, and
leveraging advanced formatting options and design principles.

7. Explain the concept of data lineage in Power BI and its importance in data governance?

Data lineage in Power BI refers to the end-to-end documentation of data flow from source to
destination, including transformations and dependencies. It is important for data governance as it
provides transparency, traceability, and accountability in data processes.

8. What are the benefits of using Power BI Embedded for application embedding scenarios?

Power BI Embedded allows developers to integrate Power BI reports and dashboards directly into
custom applications, providing seamless analytics capabilities without requiring users to leave the
application environment. It offers scalability, customization, and white-labeling options for
embedding scenarios.

9. How can you optimize Power BI reports for mobile devices?

Optimizing Power BI reports for mobile devices involves designing responsive layouts, simplifying
visuals for smaller screens, prioritizing key insights, and leveraging features like drill-through and
bookmarks for interactive exploration on mobile devices.

10. Explain the process of data lineage in Power BI and its significance in regulatory compliance.

Data lineage in Power BI involves documenting the flow of data from its source to its
consumption, including transformations and dependencies. It is significant in regulatory compliance
as it ensures transparency, auditability, and accountability in data processes, helping organizations
meet regulatory requirements such as GDPR or HIPAA.


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