Momentum One Academy · lab
Design and Implement a Dimensional Model
This intermediate lab uses a retail sales scenario to build a dimensional Warehouse model. Participants explore how a clear fact-table grain and descriptive dimensions support analysis, then compare a correction that overwrites a value with a change that preserves its history.
What the lab covers
- Structuring sales facts with date, store, product and customer dimensions.
- Reviewing key constraints as relationship metadata in Fabric Warehouse.
- Querying sales by time, product category, region and customer segment.
- Comparing SCD Type 1 overwrite behavior with SCD Type 2 historical versioning.
- Reviewing how fact rows connect to the appropriate dimensional version.
Learning outcome
Participants can explain the purpose of fact and dimension tables, identify the grain of a sales fact, and choose between overwrite and historical tracking patterns based on the business question. They also learn that the key constraints in this lab document relationships but are not enforced as database integrity checks.
Workshop connection
This overview supports Module 08 — Direct Lake, Semantic Models, Copilot & Data Agents. It complements semantic-model design by focusing on the Warehouse layer beneath analytical models and on the history choices that affect reporting.
Access note
The exercise requires a Fabric paid or trial capacity and permission to create a Warehouse. The detailed guide, SQL and working data are supplied during training. This overview does not publish the PDF or participant instructions.
Further learning
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