Here, we will discuss Power BI Interview Questions and Answers PDF, which interviewers mainly ask for Data Analysts, MIS Analysts & Consultants in company interviews.
Table of Contents
1. What is Power BI?
Power BI is Microsoft’s business analytics tool for visualizing data, generating insights, and sharing reports. It integrates with multiple data sources, transforms raw data via Power Query, and creates interactive dashboards.
With DAX for calculations, cloud collaboration via Power BI Service, and mobile access, it enables data-driven decisions for technical and non-technical users.
2. Power BI Interview Topics
- Core Concepts: Data modeling, relationships (star schema), ETL with Power Query.
- DAX: Formulas, time intelligence, calculated columns vs. measures.
- Visualization: Best practices, custom visuals, drill-through, bookmarks.
- Technical: Row-level security, performance optimization, data gateways.
- Deployment: Publishing reports, Power BI Service vs. Desktop, sharing dashboards.
- Advanced: DirectQuery vs. Import, incremental refresh, integration (Azure, Excel).
- Scenario-Based: Troubleshooting data issues, real-time analytics, translating business requirements into solutions
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Power BI Interview Questions and Answers PDF
1. How would you design a data model for a project with multiple fact tables?
Design a star schema or snowflake schema. Each fact table should have relationships to shared dimension tables, ensuring the model remains easy to understand and efficient for querying.
2. What are the best practices to optimize large datasets in Power BI?
- Use DirectQuery when datasets are too large to import.
- Optimize data models by removing unnecessary columns and rows.
- Utilize Aggregation tables to improve performance.
- Enable Columnar Compression with the VertiPaq engine.
- Use Query Folding to push data transformations to the source database.
3. How do you handle dynamic row-level security (RLS) for global users?
Implement RLS by creating security roles within Power BI Desktop. Use DAX to filter data dynamically based on user attributes such as region, department, or location. The security logic can be driven by user-specific data from a lookup table.
4. What’s the difference between DirectQuery and Import Mode? When would you use each?
- DirectQuery: Queries data in real time from the source, ideal for large datasets where data cannot be fully loaded into memory.
- Import Mode: Loads data into Power BI’s in-memory model, offering faster performance for smaller datasets or when you need to do heavy calculations.
5. How do you resolve many-to-many relationships in Power BI?
Use a bridge table (also known as a fact-less fact table) to resolve many-to-many relationships. This table holds unique keys from both fact tables and allows for correct aggregation.
6. Explain the difference between calculated columns and measures. When should you use each?
- Calculated Columns: These are used to create new data at the row level, added to your table, and stored in the data model. They are calculated during data refresh and remain static.
- Measures: Measures are used for aggregating data dynamically at the query level. They are calculated on the fly based on applied filters, slicers, and user interactions.
7. What strategies do you use to troubleshoot performance issues in Power BI reports?
- Analyze Query Performance: Utilize tools like DAX Studio to assess query performance.
- Optimize DAX Calculations: Identify and optimize complex DAX formulas that might be slowing down report performance.
- Reduce Heavy Visuals: Minimize the use of visuals with large datasets or complex calculations that can impact report speed.
- Optimize Data Model: Review relationships and remove unnecessary columns or tables to streamline the model.
8. How would you implement incremental data refresh in Power BI?
Configure Incremental Refresh in Power BI Desktop to refresh only new or modified data. Then, apply the refresh policy in Power BI Service and define partitions for a more efficient refresh process.
9. What is the role of the VertiPaq engine in Power BI?
The VertiPaq engine is an in-memory storage engine that compresses data into optimized columnar formats.
This enables faster querying and enhances performance, particularly when working with large datasets in Power BI.
10. How do you manage and schedule data refreshes for large-scale dashboards?
In Power BI Service, set up scheduled refresh to automate updates. For large-scale dashboards, break the refresh into smaller partitions and implement Incremental Refresh to avoid full data reloads, improving overall refresh efficiency.
11. How would you visualize sales trends over time and forecast future values in Power BI?
Use a line chart to visualize sales trends, and leverage Power BI’s forecasting feature to predict future sales based on historical data.
12. How would you restrict users’ access to data so they can only view the sales data for their specific region?
Implement Row-level Security (RLS) by defining security roles and applying DAX filters based on region to restrict user access to only relevant data.
13. How would you highlight low-profit products in Power BI using conditional formatting?
Apply conditional formatting to a table or matrix visual, using rules to highlight products with low-profit margins (e.g., red for low profit).
14. How would you create a drill-through page in Power BI to analyze customer-specific details?
Create a drillthrough page, add a field like CustomerID, and allow users to right-click on a customer in the main report to drill down into detailed data.
15. How would you clean and transform messy data with duplicate rows and inconsistent formats in Power BI?
Use the Power Query Editor to remove duplicates, standardize data formats, and apply necessary transformations for a cleaner dataset.
16. How would you create a dynamic filter to display data for the last 7 days in a Power BI report?
Create a DAX measure that calculates the date range for the last 7 days, using functions like `TODAY()` and `DATEADD()`, then apply it as a filter or slicer.
17. How would you compare target vs. actual sales and visualize the variance in Power BI?
Use a clustered column chart to compare target vs. actual sales, and calculate the variance with a simple DAX measure for clearer insights.
18. How can you set up real-time alerts in Power BI for specific KPIs (e.g., profit margin falling below 10%)?
Set up real-time alerts on KPI visuals in Power BI Service to notify you when a KPI, like profit margin, falls below a threshold.
19. How would you calculate and display a weighted average in Power BI?
Use a DAX formula to calculate the weighted average: `(SUMX(Column, Value * Weight) / SUM(Weight))` and display it in a card or chart.
20. How would you handle matching customer addresses with slight variations (e.g., abbreviations) in Power BI?
Use Power Query transformations like Text.Upper(), Text.Replace(), and fuzzy matching techniques to standardize and reconcile address variations.
21. Find the Top 5 Customers with the Highest Total Purchase Amount:
Assume you have two tables: Customers (CustomerID, Name) and Orders (OrderID, CustomerID, Amount).
SELECT c.CustomerID, c.Name, SUM(o.Amount) AS TotalPurchase FROM Customers c JOIN Orders o ON c.CustomerID = o.CustomerID GROUP BY c.CustomerID, c.Name ORDER BY TotalPurchase DESC LIMIT 5;
22. Find the nth Highest Salary from a Table:
-- Replace `n` with the desired rank (e.g., 2 for the second highest). SELECT DISTINCT Salary FROM Employees ORDER BY Salary DESC LIMIT 1 OFFSET n-1;
23. Find the Total Quantity Sold for Each Product Per Month:
Given a table Sales (SaleID, ProductID, SaleDate, Quantity), the query would be:
SELECT ProductID, DATE_TRUNC('month', SaleDate) AS Month,
SUM(Quantity) AS TotalQuantity
FROM Sales
GROUP BY ProductID, Month
ORDER BY ProductID, Month;
