Power BI Data Modeling & DAX Questions
Understand Power BI's data modeling concepts: relationships (one-to-many, many-to-many), cardinality, filter propagation, and bidirectional relationships. Write DAX formulas for measures and calculated columns, including basic (SUM, COUNT, AVERAGE) and advanced functions (CALCULATE, FILTER, ALL, VALUES). Understand variables and performance implications of DAX formulas.
MediumSystem Design
0 practiced
You must allow users to slice reports by either Order Date or Ship Date simultaneously while preserving correct measures. Propose a data model and DAX pattern that supports both slicers without duplicating measures, mentioning disconnected slicers, USERELATIONSHIP, SWITCH logic, or TREATAS where appropriate.
MediumTechnical
0 practiced
Create a DAX measure to compute a running total of Sales Amount by month partitioned by ProductCategory that respects filters on ProductCategory but ignores any filters applied to SalesRep. Model: Sales(Date, ProductID, SalesRepID, Amount), Product(ProductID, ProductCategory).
HardTechnical
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Discuss trade-offs of creating composite keys via concatenated calculated columns versus generating integer surrogate keys in ETL for relationships in Power BI. Explain effects on VertiPaq compression, cardinality, join performance, and complexity of DAX measures.
HardTechnical
0 practiced
You inherit a Power BI dataset mixing Import and DirectQuery tables. Visual totals are incorrect and performance is poor due to ambiguous relationships and bidirectional filters. Describe diagnostic steps, model changes, and DAX fixes you would apply to correct totals and minimize performance regressions.
HardTechnical
0 practiced
A measure uses SUMX over a SUMMARIZE that includes many columns and performs slowly. Propose a refactor using SUMMARIZECOLUMNS, ADDCOLUMNS, or GROUPBY and provide the refactored DAX pattern. Explain why the refactor improves performance and how it interacts with existing measures.
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