Power BI Interview Questions and Answers for Analyst Roles

Power BI is Microsoft's business intelligence tool for connecting to data, modeling it, and building interactive reports. Its main parts are Power BI Desktop (authoring), the Power BI Service (sharing online), and Power BI Mobile for viewing.

DAX (Data Analysis Expressions) is the formula language in Power BI used to create measures, calculated columns, and calculated tables. It includes functions for aggregation, filtering, and time intelligence that operate over the data model.

A calculated column is computed row by row and stored in the model, using memory. A measure is computed on the fly at query time based on the current filter context, so it's more efficient for aggregations like totals and ratios. Prefer measures for aggregates.

Power Query is Power BI's data transformation layer, used to connect, clean, and shape data before it loads into the model. Its steps are recorded in the M language. Transformations here happen before DAX and the data model.

Import mode loads a copy of the data into Power BI's in-memory engine for fast performance but needs refreshes. DirectQuery leaves data in the source and queries it live, giving real-time data at the cost of slower interactions and some feature limits.

A star schema has a central fact table (transactions/metrics) linked to surrounding dimension tables (date, product, customer). It's recommended because it makes relationships simple, DAX easier to write, and the model faster than a flat or snowflake design.

Row context is the current row being evaluated, used in calculated columns and iterators. Filter context is the set of filters applied by visuals, slicers, and CALCULATE. Understanding how they interact is the key to correct DAX.

CALCULATE evaluates an expression under a modified filter context. It's the most important DAX function because it lets you add, remove, or change filters — for example, computing sales for a specific region or ignoring a slicer.

SUM aggregates a single column directly. SUMX is an iterator that evaluates an expression row by row and then sums the results, so use it when the value depends on multiple columns, like quantity times price.

Relationships connect tables on a key, usually one-to-many from a dimension to a fact table, with a filter direction (single or both). Correct one-to-many relationships let filters flow from dimensions to facts so measures aggregate correctly.

Time intelligence functions (TOTALYTD, SAMEPERIODLASTYEAR, DATEADD) compute period-based calculations like year-to-date and year-over-year. They require a marked, continuous date table in the model to work reliably.

RELATED pulls a single value from the one-side of a relationship into the many-side (like a lookup). RELATEDTABLE returns the related rows from the many-side and is typically used inside an iterator to aggregate them.

A dedicated, continuous date dimension marked as a date table enables time-intelligence functions, ensures no missing dates break calculations, and lets you add useful attributes like fiscal year, quarter, and weekday for consistent reporting.

VAR stores the result of an expression within a measure so it's computed once and reused. Variables make DAX more readable, avoid recalculating the same logic, and prevent context-transition surprises, improving both clarity and performance.

RLS restricts the data a user can see by applying DAX filter rules to roles — for example, a regional manager sees only their region. Roles are defined in Desktop and members are assigned in the Service.

Context transition happens when CALCULATE (or a measure reference) turns the current row context into an equivalent filter context. It's why a measure called inside an iterator like SUMX evaluates for the current row.

Use a star schema, prefer measures over calculated columns, reduce cardinality, remove unused columns and tables, push heavy transformations into Power Query or the source, limit visuals per page, and use variables in DAX to avoid recomputation.

ALL removes all filters from a table or columns; ALLEXCEPT removes filters except the columns you list; REMOVEFILTERS (the modern equivalent of ALL as a filter modifier) clears filters within CALCULATE. They're used to compute totals or percentages of a whole.

USERELATIONSHIP activates an inactive relationship for a specific calculation inside CALCULATE — useful when a fact table has multiple date columns (order date, ship date) and you want a measure to use a different one.