Power BI Data Modelling: Flat Tables vs Star Schemas Explained

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Data modelling in Power BI involves defining relationships between tables and organising data structures to support effective analysis, DAX calculations, and report performance. A flat table stores all data in a single denormalised structure, making it simple to build but prone to redundancy, slow queries, and poor scalability as data grows. In contrast, a star schema separates data into fact tables and dimension tables, placing the fact table at the centre and connecting dimensions directly to it. This structure is better suited to Power BI's storage and query engines, enabling simpler DAX measures, faster filter propagation, and easier maintenance. While flat tables may suit very small datasets, star schemas are the recommended approach for any analytics work that requires scalability and reusability.

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