Power BI Interview Question Categories
Power BI interviews typically cover five areas:
- Fundamentals: What Power BI is, components (Desktop, Service, Gateway, Mobile)
- Data Connectivity: DirectQuery vs. Import mode, data source types
- Data Modelling: Star schema, relationships, cardinality, cross-filter direction
- DAX: Measures vs. calculated columns, CALCULATE, FILTER, time intelligence functions
- Report Design: Visuals, row-level security, performance optimisation, publishing
Core DAX Concepts
DAX (Data Analysis Expressions) is the most tested skill in Power BI interviews:
- CALCULATE() — the most powerful DAX function; modifies filter context
- SUMX() vs. SUM() — understand when to use iterator functions
- RELATED() — bring values from related tables
- USERELATIONSHIP() — activate inactive relationships in calculations
- Time intelligence: TOTALYTD, SAMEPERIODLASTYEAR, DATEADD, DATESYTD
- RANKX() — dynamic ranking within a filter context
- Variables (VAR...RETURN) — improve DAX readability and performance
- ALLEXCEPT() vs. ALL() — remove specific vs. all filter context
Data Modelling Concepts
Senior Power BI roles heavily test data modelling knowledge:
- Star schema vs. snowflake schema — why star schema is preferred in Power BI
- Dimension and fact tables — how to identify and model them
- Relationship types: one-to-many, many-to-many
- Cross-filter direction: single vs. bidirectional — risks of bidirectional
- Role-playing dimensions using inactive relationships
- Date table: why you need one, how to mark it, CALENDAR() function
- Row-level security (RLS): static vs. dynamic, how to test it
DirectQuery vs. Import Mode
A very common interview question for Power BI developers:
- Import: Data loaded into Power BI memory. Fast performance. Refresh required for new data.
- DirectQuery: Queries sent to source in real time. Always current. Slower performance.
- Composite model: Mix of Import and DirectQuery in one model
- When to use Import: Static or slowly changing data, performance is critical
- When to use DirectQuery: Real-time data required, data governance reasons
- Limitations of DirectQuery: No calculated columns in Power Query, DAX functions limited
Common Interview Questions & Answers
Q1. What is the difference between a measure and a calculated column?
A calculated column is computed row by row during data refresh and stored in the model — it adds a permanent column to the table. A measure is calculated on the fly during report interaction based on the current filter context — it is not stored and does not increase model size. Use measures for aggregations; use calculated columns only when you need row-level values for filtering or grouping.
This is asked in almost every Power BI interview. Know both use cases cold.
Q2. Explain CALCULATE() in DAX.
CALCULATE() evaluates an expression in a modified filter context. The first argument is the expression to calculate; subsequent arguments are filter modifiers. For example, CALCULATE(SUM(Sales[Amount]), Sales[Region] = 'North') calculates total sales but only for the North region, regardless of any other filter on the report.
Demonstrate with a concrete example — don't just define it.
Q3. What is row-level security in Power BI?
Row-level security restricts data access at the row level based on the user's identity. Static RLS: you define fixed rules for each role. Dynamic RLS: uses DAX (USERNAME() or USERPRINCIPALNAME()) to filter data based on who is logged in. You set it up in Power BI Desktop and publish to the Service where users are assigned to roles.
Know how to test RLS in Power BI Desktop using 'View as Role'.
Common Mistakes to Avoid
Confusing measures and calculated columns — the most common fundamental error
Using bidirectional relationships everywhere — causes ambiguity and slow performance
Not having a dedicated date table — breaks all time intelligence functions
Using DirectQuery when Import mode would suffice — unnecessary performance penalty
Not understanding the difference between row context and filter context in DAX
Expert Tips
Build a portfolio of 3–4 Power BI dashboards on public datasets — upload to GitHub
Get the PL-300 Microsoft Power BI Data Analyst certification
Practice explaining your reports — Power BI roles require strong communication with stakeholders
Know the Power BI Service features: workspaces, apps, scheduled refresh, dataflows
Pre-Interview Checklist
6 itemsFrequently Asked Questions
Is Power BI certification worth it for interviews?
Yes — the PL-300 certification is well-recognised and demonstrates structured knowledge. Many job postings now list it as 'preferred'. It is worth earning before applying to Power BI developer roles.
What is the difference between Power BI and Tableau?
Power BI is Microsoft's tool — better integrated with the Office 365/Azure ecosystem, more affordable. Tableau is platform-agnostic, stronger in data visualisation flexibility, and more popular in Western markets. India's enterprise market increasingly uses Power BI.
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