Power BI interviews go beyond "can you build a chart" — they test the data modeling and DAX that power real dashboards, plus Power Query for data prep. Here are the Power BI interview questions that actually get asked. (See also our data analyst guide.)
Data modeling
- What is a star schema, and fact vs dimension tables?
- Relationships — one-to-many, cardinality, and cross-filter direction.
- Star schema vs snowflake schema.
- Why is a good data model the foundation of a good report?
DAX (the core)
- Calculated columns vs measures — the key difference.
- Row context vs filter context.
- CALCULATE — why it's the most important DAX function.
- Common functions — SUMX, FILTER, RELATED, time intelligence (e.g. SAMEPERIODLASTYEAR).
Power Query & reports
- What is Power Query (M) used for — ETL and transformations?
- Merge vs append queries.
- Import vs DirectQuery mode.
- Report design and performance optimization.
How to prepare
Power BI rounds probe DAX and modeling concepts verbally. Practise explaining measures vs columns and filter context out loud. Greenroom runs spoken technical interviews that follow up on your reasoning. Pair it with our data analyst and Tableau guides.
Frequently asked questions
What questions are asked in a Power BI interview?
Power BI interviews cover data modeling (star schema, fact vs dimension tables, relationships and cardinality, star vs snowflake), DAX (calculated columns vs measures, row vs filter context, CALCULATE, functions like SUMX, FILTER, RELATED and time intelligence), Power Query (M for ETL, merge vs append), Import vs DirectQuery mode, and report design and performance optimization.
What is the difference between a calculated column and a measure in Power BI?
A calculated column is computed row by row when data loads and is stored in the model, using row context — useful for static, per-row values you can slice by. A measure is calculated on the fly at query time based on the current filter context, so it responds dynamically to slicers and visuals — used for aggregations like total sales. Measures are generally preferred for performance and flexibility.
What is DAX in Power BI?
DAX (Data Analysis Expressions) is the formula language for creating measures and calculated columns in Power BI. It works with row context and filter context, and its most important function is CALCULATE, which modifies the filter context of a calculation. Mastering DAX — especially how context flows — is what separates strong Power BI developers from people who only build basic visuals.
How should I prepare for a Power BI interview?
Focus on the layer beneath the visuals: a clean star schema and correct DAX, especially the difference between calculated columns and measures, row vs filter context, and CALCULATE, plus Power Query for data prep. Practise explaining these concepts out loud with a voice-based mock interview that follows up, since Power BI rounds probe modeling and DAX understanding.