Top 8 Power BI Interview Questions
Table of Contents
Introduction
If you have been preparing for a Power BI interview by reading generic questions list, you have probably noticed something; half of them never come up in real interviews, and the ones that do come up are not explained well. This post is built around what candidates report being asked from HR screens to technical rounds to live “build this in front of us” exercises.
The Warm-Up Questions
These questions are asked almost every time in the interviews, usually to screen out and shortlist candidates.
- What is Desktop vs. Service?
Power BI Desktop is where you build, connect data, model it, write DAX, and design reports. Power BI Service is where you publish, share, schedule refreshes, and enforce security.
- What is the difference between Report and a Dashboard?
A report is multi-page and interactive, built on one dataset. A dashboard is a single-page collection of pinned tiles that can you pull from multiple reports, but tiles aren’t interactive in the same way.
- What is Calculated column vs. Measure?
This is one of the most common questions asked in interviews.
- A calculated column is evaluated row by row during data refresh, and its results are stored in the model, which increases memory usage.
- A measure computes at query time based on current filter context and isn’t stored.
Use columns when you need a sliceable field; use measures for anything aggregated.
Note: Checkout our blog: Calculated Columns or Calculated Measures? What’s the best choice?
- What is an iterator function?
Functions like SUMX(), AVERAGEX(), RANKX() that evaluate row-by-row before aggregating. They are used when the calculation itself (like quantity x price) isn’t a stored column.
Note: Check out our blogpost for more information on iterator functions: Basic Iterators in DAX: AVERAGEX(), MINX() & MAXX()
Data Modeling Questions
- What is Star vs. Snowflake Schema?
• Star: Fact table connected directly to denormalized dimensions.
• Snowflake: Dimensions split further into sub-tables.
Interviewers want to hear you prefer star schema; better VertiPaq performance, simpler DAX, and fewer relationship hops.
Note: Checkout our blog: Schemas in a Data Model
- What is Filter context vs. row context?
• Row context exists in calculated columns and iterators like SUMX().
• Filter context tells which subset of data is visible, shaped by slicers and filters.
Strong answers mention how CALCULATE() triggers context transition between the two.
Note: For more information checkout our blogpost: Row Context & Filter Context: Evaluation Context in DAX
- What are Active vs. inactive relationships?
Only one active relationship per table pair; extras stay inactive and get activated with USERELATIONSHIP() inside a measure. Classic example: Order Date vs. Ship Date, both linking to a Date table.
Note: Check out our blog: Active vs. Inactive Relationship in a Data Model
DAX Questions
- Write a YTD sales measure.
Sales YTD =
TOTALYTD ( SUM ( Sales[Amount] ), ‘Date'[Date] )
Often followed by: “now do it manually with CALCULATE and DATESYTD” to test if you understand what’s happening under the hood.
- What is CALCULATE() vs. FILTER()?
CALCULATE() modifies filter context. FILTER() returns a filtered table and usually sits inside CALCULATE() for row-by-row logic that simple conditions can’t express.
- What is Running total?
Running Total =CALCULATE (
SUM ( Sales[Amount] ),
FILTER ( ALL ( ‘Date’ ), ‘Date'[Date] <= MAX ( ‘Date'[Date] ) )
)
- What are ALL(), ALLEXCEPT() and ALLSELECTED()?
ALL() clears all filters on a table/column. ALLEXCEPT() clears all except what you specify. ALLSELECTED(), the one people get wrong, respects filters from outside a visual while ignoring ones added inside it; it’s the go-to for “% of total within current selection.”
Note: Refer to our blog for more information: Use ALLSELECTED() in Power BI to Fix Incorrect Total Calculations
Power Query Questions
- Power Query vs. DAX, when do you use which?”
- Power Query (M) shapes data before loading; cleaning, merging, and pivoting.
- DAX is used on data already loaded. Rule of thumb: if it can be done in Power Query, do it there
Note: Check out our blogpost for more information: Learn How to Write DAX Queries in DAX Studio Using Query Builder
- Merging tables with different granularities?
Expect to discuss join types (Left Outer is common) and aggregating the higher-granularity table first to avoid row duplication.
- Query parameters?
Make queries dynamic and reusable. For example, a parameter for environment or date range, so logic doesn’t need editing by hand.
Performance & Optimization Questions
- Troubleshoot a report that is running slow?
It is an open-ended question; process matters more than one right answer. Strong responses mention:
Performance Analyzer, checking for nested DAX (especially CALCULATE() inside iterators), reviewing bidirectional relationships, and considering aggregations or a composite model if data volume is the real issue.
- What is VertiPaq?
It is an in-memory columnar engine in Power BI that uses compression to store and process data efficiently.
- What is a composite model?
Composite models mix Import and Direct Query sources; large tables stay in Direct Query, smaller reference tables get imported for speed.
Security & Governance Questions
- How does RLS work?
Start by defining roles in Desktop with DAX filter expressions (e.g., [Region] = USERNAME()), then assigning users to roles in the Service. Mention static RLS (hardcoded values) vs. dynamic RLS (driven by a mapping table tied to the logged-in user).
Note: Check out our post: Power BI Row-Level Security (RLS): Static vs Dynamic Approaches
- What is Workspace vs. app?
A workspace is the collaborative back-end for building. An app is a packaged, read-only distribution pushed to a wider audience.
Note: Checkout our blogpost on Power BI Workspace: Understanding Workspaces in Power BI Service: A Complete Guide
“Prove You've Actually Used It” Questions
Common in take-homes and live interviews: “Build a dashboard from this dataset in 20 minutes,” or “debug why this measure isn’t updating with a slicer.”
It is interviewers’ way to analyze your thinking process: check the data model first, use DAX Studio or Performance Analyzer, ask clarifying questions about what “correct” should look like.
Behavioral Questions
- A stakeholder asked for something that wasn’t a good idea; what did you do?
Tests diplomatic pushback, e.g., a 15-category pie chart, or an undefined metric.
- Conflicting requirements between two departments in the same report?
It is more about navigating ambiguity without building five versions of “the truth.”
Conclusion
Power BI interviews rarely test how many functions you’ve memorized; they test whether you understand why the tool behaves the way it does. That’s why the same questions keep resurfacing: calculated columns vs. measures, filter context vs. row context, star vs. snowflake. Walk in with solid modelling fundamentals, a working grasp of DAX’s evaluation logic, and one or two real project stories, and you’ll be ready for most of what actually gets asked, including live-build exercises that trip up candidates who only memorized definitions.
FAQs
The most common questions cover Power BI Desktop vs Service, reports vs dashboards, DAX measures, calculated columns, filter context, row context, star schema, Power Query, data modeling, report optimization, and Row-Level Security (RLS).
Yes. Most technical interviews include DAX questions such as CALCULATE(), FILTER(), SUMX(), TOTALYTD(), ALL(), and time intelligence functions. Interviewers also expect you to understand filter context and row context.
Practice building dashboards, write DAX measures from scratch, understand data modeling concepts, learn Power Query transformations, and be ready to explain your real-world Power BI projects.
Further Learning and Resources
To learn more about Power BI, check out our courses here:
- Power BI Essentials
- Power BI Report Design
- Power BI Advanced
- Power BI DAX Essentials
- Power BI Service Course
- Chat GPT Essentials
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How do you publish and manage reports in Power BI Service?
Hi, you can remember this simple workflow: Power BI Desktop → Validate → Workspace → Semantic Model → Refresh & Security → App/Sharing → Deployment → Monitoring I follow this workflow to make sure the report is not only published but also accurate, secure, accessible, and properly maintained. After building and validating the report in Power BI Desktop, I publish it to the appropriate workspace, configure the semantic model, refresh schedule, and security. Then I share it with users through an app or appropriate permissions. Finally, I monitor refreshes, performance, and user feedback and make updates when needed. Hope it helps!!
Hi, you can remember this simple workflow:
Power BI Desktop → Validate → Workspace → Semantic Model → Refresh & Security → App/Sharing → Deployment → Monitoring
I follow this workflow to make sure the report is not only published but also accurate, secure, accessible, and properly maintained. After building and validating the report in Power BI Desktop, I publish it to the appropriate workspace, configure the semantic model, refresh schedule, and security. Then I share it with users through an app or appropriate permissions. Finally, I monitor refreshes, performance, and user feedback and make updates when needed. Hope it helps!!