Power BI Data Modelling: How Fact and Dimension Tables Drive Accurate Insights

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Data modelling in Power BI involves structuring datasets into a framework that ensures accuracy, optimises performance, and simplifies reporting. Rather than storing all data in a single flat table, the approach separates information into fact tables, which hold quantitative transactional data, and dimension tables, which provide descriptive context. Relationships between these tables allow filters and calculations to flow predictably, making DAX formula writing more reliable and less error-prone. Key design decisions around granularity, cardinality, and entity relationships determine how data is split and organised across tables. A well-built model is also scalable, allowing new data sources or metrics to be added without rebuilding the entire structure.

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ProgrammingDEV Community ·

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