Data Modelling Fundamentals: Schemas, Relationships, and Joins Explained

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Data modelling is the process of defining database tables and establishing relationships between them, with the goal of simplifying analysis, improving query performance, and reducing complexity. Common structural approaches include flat tables, star schemas, and snowflake schemas, each offering different trade-offs in performance, file size, and query complexity. Fact tables store measurable transactional data while dimension tables provide descriptive context, and cardinality defines how rows in one table numerically relate to rows in another. Relationships between tables rely on primary and foreign keys, with filter direction and active relationship settings manageable directly within tools like Power BI. In Power Query, data can be combined either by merging tables side by side into a wider table or by appending rows to create a longer one, with the chosen join type determining which records are retained.

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