Interview Prep:

As an intermediate-level Power BI developer, you're expected to have a solid grasp of data modeling, DAX, advanced visualizations, and performance optimization. Here are the top 20 questions you’re likely to encounter in an interview, along with expert-level answers that demonstrate your expertise.

1. What is the difference between a star schema and a snowflake schema, and which is better for Power BI?

Answer:

• Star Schema: A central fact table is connected directly to dimension tables. It is simpler and more efficient for Power BI as it minimizes joins, improving performance.

• Snowflake Schema: Dimension tables are normalized into multiple related tables. While it reduces redundancy, it can complicate queries and slow down performance in Power BI.
  Recommendation: Use star schema for most Power BI implementations.

2. How do you handle performance issues in Power BI?

Answer:

1. Optimize the data model by reducing the number of columns and using appropriate data types.

2. Use measures instead of calculated columns where possible.

3. Aggregate data to minimize the dataset size.

4. Avoid complex DAX expressions and use variables for reusable logic.

5. Leverage performance analyzer in Power BI to identify bottlenecks.

3. What are aggregations in Power BI, and how do you use them?

Answer:
Aggregations are precomputed summaries of data stored in the model to improve query performance. In Power BI, they are used to optimize reports by storing summarized data (e.g., SUM, COUNT) while keeping the granular data for drill-through.

4. Explain the CALCULATE function and its importance in Power BI.

Answer:
CALCULATE modifies the filter context of a measure or calculation. It is a powerful function for creating dynamic calculations.
Example:
CALCULATE(SUM(Sales[Amount]), Year = "2023") calculates the total sales amount for the year 2023.

5. What is the difference between ALL, ALLEXCEPT, and REMOVEFILTERS in DAX?

Answer:

• ALL: Removes all filters from a column or table.

• ALLEXCEPT: Removes all filters except for the specified columns.

• REMOVEFILTERS: Removes filters but can preserve the context introduced by other DAX functions.

6. How do you implement dynamic measures in Power BI?

Answer:
Dynamic measures can be created using disconnected tables and the SWITCH function.
Example:
Using a parameter table to allow users to switch between "Total Sales" and "Profit" in a visualization.

7. How do you handle time intelligence in Power BI?

Answer:

1. Use a dedicated Date table with continuous dates and mark it as a Date Table.

2. Utilize DAX functions like TOTALYTD, SAMEPERIODLASTYEAR, and DATESBETWEEN for time-based calculations.

8. What is Direct Query, and when would you use it?

Answer:
Direct Query allows Power BI to fetch data directly from the source without importing it. It is suitable when:

• The dataset is too large for in-memory storage.

• Real-time data updates are required.

• Security policies are enforced at the data source.

9. What are the limitations of DirectQuery?

Answer:

1. Slower performance compared to Import mode.

2. Limited use of DAX functions.

3. Dependent on source system performance and query limits.

4. Data transformations are restricted.

10. What is incremental data refresh in Power BI, and how does it work?

Answer:
Incremental refresh updates only the new or changed data during a refresh cycle, rather than reloading the entire dataset. It is configured in Power BI Desktop and managed in the service, using parameters for partitioning.

11. How do you troubleshoot visual issues in Power BI?

Answer:

1. Use Performance Analyzer to identify slow visuals.

2. Check data relationships for correctness.

3. Validate filters and slicers applied to the visual.

4. Simplify calculations or replace complex visuals.

12. How do you optimize relationships in a data model?

Answer:

1. Use single-direction relationships unless bi-directional is necessary.

2. Create relationships on surrogate keys rather than text columns.

3. Avoid circular references by restructuring the model.

13. What are composite models in Power BI, and why are they useful?

Answer:
Composite models allow combining DirectQuery and Import mode in a single dataset. This flexibility is useful for combining real-time and historical data in a report.

14. How do you implement role-based security in Power BI?

Answer:

1. Define roles in Power BI Desktop with DAX expressions to filter data.

2. Assign users to roles in the Power BI Service.

15. What is a calculated table, and when would you use it?

Answer:
A calculated table is created using DAX expressions and is stored in the data model. Use it for scenarios like:

• Creating summary tables.

• Generating lookup tables from existing data.

16. How do you handle many-to-many relationships in Power BI?

Answer:

1. Use a bridge table to resolve many-to-many relationships.

2. Enable bi-directional filtering if necessary, but carefully manage its impact on performance.

17. What are custom visuals, and how do you create or use them?

Answer:
Custom visuals are additional visuals downloaded from the Power BI Marketplace or developed using the Power BI Developer Tools. They allow more flexibility than default visuals.

18. Explain the difference between Publish to Web and Share Report in Power BI.

Answer:

• Publish to Web: Makes the report publicly accessible without authentication.

• Share Report: Shares the report securely with specific users via the Power BI Service.

19. How do you handle common DAX errors?

Answer:

1. Circular dependency: Refactor calculated columns or measures.

2. Ambiguous relationships: Check data model relationships.

3. Invalid function: Validate syntax and check for unsupported functions in Direct Query.

20. How do you ensure scalability in Power BI reports?

Answer:

1. Use star schema for data modeling.

2. Optimize DAX queries for performance.

3. Minimize visuals and unnecessary interactions.

4. Use aggregations and incremental refresh for large datasets.

Conclusion

These questions cover the advanced concepts, practical challenges, and performance optimizations that intermediate Power BI developers encounter. By understanding and practicing these scenarios, you’ll be well-prepared to demonstrate your expertise and excel in your role as a seasoned Business Intelligence professional.