Power BI Interview Practice Questions and Answers is the ultimate resource I’ve designed for data professionals who want to move beyond surface-level tutorials and truly master the mechanics of enterprise business intelligence. I’ve built this question bank to bridge the gap between "knowing the buttons" and "understanding the logic," ensuring you can confidently navigate high-stakes interviews or certification exams by deeply exploring everything from Star Schema optimization to complex DAX filter context. Whether you are struggling with the nuances of Row-Level Security, the performance implications of bidirectional relationships, or the intricacies of Power Query M transformations, I provide the granular, "why-behind-the-what" explanations you need to think like a Senior Power BI Developer. By focusing on real-world scenarios rather than rote memorization, I help you develop the architectural mindset required to build scalable, high-performance reporting solutions that stakeholders actually trust.

Exam Domains & Sample Topics

Power BI Fundamentals & Data Modeling: Star vs. Snowflake, Cardinality, and Normalization.
DAX Mastery: CALCULATE, Time Intelligence, Iterators (SUMX), and Context Transition.
Power Query & ETL: M Language, Incremental Refresh, and API Integrations.
Visualization & UX: Bookmarks, Drill-through, and Dashboard Storytelling.
Power BI Service & Security: RLS, Deployment Pipelines, Gateways, and Governance.

Sample Practice Questions

Question 1: You are designing a data model for a large retail chain. You have a fact table with 100 million rows and a high-cardinality dimension table. Which relationship setting is best for performance and model stability?
Question 2: Which DAX function would you use to modify the filter context of a calculation to ignore all filters applied to a specific column while keeping filters on other columns?
- A) ALL()
- B) ALLEXCEPT()
- C) ALLSELECTED()
- D) REMOVEFILTERS()
- E) KEEPFILTERS()
- F) VALUES()
- Correct Answer: D
- Overall Explanation: While several functions deal with filters, REMOVEFILTERS is the modern, explicit DAX function specifically designed to clear filters from a designated table or column within a CALCULATE statement.
- Detailed Option Analysis:
  - A) Incorrect: ALL() works, but it is also used to return a table of unique values. REMOVEFILTERS is the preferred semantic choice for "filter removal" inside CALCULATE.
  - B) Incorrect: ALLEXCEPT() removes all filters except for the specified columns, which is the opposite of the requirement.
  - C) Incorrect: ALLSELECTED() ignores filters inside the query but respects "external" filters like slicers; it doesn't target a specific column exclusively.
  - D) Correct: REMOVEFILTERS() is specifically optimized to clear filters on a targeted column without affecting the rest of the context.
  - E) Incorrect: KEEPFILTERS() adds to the existing filter context rather than removing it.
  - F) Incorrect: VALUES() returns a one-column table of unique values; it does not remove filters.
Question 3: A report is running slowly in the Power BI Service. After checking the Performance Analyzer, you see the "DAX Query" time is very high. What is the most likely culprit?
- A) The Gateway is not updated to the latest version.
- B) There are too many visuals on a single report page.
- C) A measure is using an iterator like SUMX over a large fact table with complex logic.
- D) The data source is an Excel file stored on OneDrive.
- E) The "Auto Date/Time" setting is enabled in Global Options.
- F) Row-Level Security (RLS) is limiting the data too aggressively.
- Correct Answer: C
- Overall Explanation: High "DAX Query" time indicates that the calculation engine is struggling to process a formula. Complex iterators (like SUMX or FILTER) force row-by-row evaluation, which can be extremely slow on large datasets.
- Detailed Option Analysis:
  - A) Incorrect: Gateway issues usually cause "Data Refresh" failures or "Data Source" latency, not slow DAX execution.
  - B) Incorrect: Too many visuals usually results in high "Other" or "Visual Display" time, not high DAX Query time.
  - C) Correct: Iterators are computationally expensive; if used over millions of rows with nested logic, they are the primary cause of slow DAX queries.
  - D) Incorrect: The source location affects refresh speed, not the runtime DAX performance of a published report.
  - E) Incorrect: Auto Date/Time increases model size (metadata), but wouldn't typically be the primary cause of a specific high DAX Query time vs. model bloat.
  - F) Incorrect: RLS actually reduces the number of rows processed, which often makes queries faster, not slower.

Welcome to the best practice exams to help you prepare for your Power BI Interview Practice Questions and Answers.
- You can retake the exams as many times as you want
- This is a huge original question bank
- You get support from instructors if you have questions
- Each question has a detailed explanation
- Mobile-compatible with the Udemy app
- 30-day money-back guarantee if you're not satisfied

I hope that by now you're convinced! And there are a lot more questions inside the course. Enroll today and take the final step toward getting certified!