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5.3.2. Data Modeling Concepts (Dimensions, Facts, Hierarchy)
💡 First Principle: A Power BI data model consists of tables, relationships, and calculations (DAX) designed to enable dynamic analysis. The model determines what questions users can ask—a poorly designed model limits insights no matter how good the visualizations are.
- Dimensions: Descriptive attributes (who, what, where, when) used to filter and group data—the "by" in "sales by region."
- Facts: Numeric, measurable data (sales amount, quantity) stored in central fact tables—the numbers you're analyzing.
- Hierarchy: A structure within a dimension that allows users to drill up and drill down (e.g., Year → Quarter → Month → Day).
- Relationship: Links between tables (typically 1:many) based on matching columns (keys).
Calculated Columns vs Measures (Critical Exam Topic!)
Both are written in DAX, Power BI's formula language, and the exam tests the difference constantly.
| Calculated Column | Measure | |
|---|---|---|
| Evaluated | Once, during data refresh | Every time a visual renders, in the current filter context |
| Stored | Yes — it becomes a real column in the model and consumes memory | No — the result is computed on demand |
| Works row by row? | Yes, it has a row context | No, it aggregates over whatever rows the filters leave |
| Can sit on an axis or in a slicer? | Yes | Generally no |
| Typical use | Categorising rows, e.g. flagging an order as "Large" or "Small" | Aggregations, e.g. Total Sales, Margin %, Year-over-Year growth |
Trap: the two are not interchangeable, and the direction is easy to reverse under exam pressure. Remember it this way: a column is baked at refresh; a measure is cooked to order. A percentage that must respond to whatever the user has filtered has to be a measure — bake it into a column and it will be wrong the moment a slicer changes.
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Written byAlvin Varughese
Founder•20 professional certifications