Data Modelling, Relationships And Joins In Power BI
Introduction This article takes through the ideas that decide whether a model works as intended Schemas; how table are organized Relationships; how the model connects tables Joins; how tables are physically combined in power query Each section on this article explains the concept, shows with an example and guidance on when to use each one of them. Data Modelling Data modelling in power BI is the…
Power BI data modelling is an essential process for connecting separate data tables so they can interact and provide accurate insights into business questions and demands. A well-designed data model ensures flexibility, ease of navigation, efficient calculations, better performance, scalability, and maintainability.
There are three main types of data models: Flat Table, Star Schema, and Snowflake Schema. Each has its advantages and disadvantages. Flat Table stores everything in a single wide table, making it simple to build but causing redundancy and performance issues. Star Schema combines a central fact table with dimension tables, providing balance, simplicity, and predictability in filtering, calculations, and readability.
Snowflake Schema is a version of the Star Schema, with dimensions further categorized into sub-dimensions, reducing repetition and simplifying data maintenance, but causing complexity in navigation and slower filtering.
Facts and dimension tables are the building blocks of a data model. Fact tables store numerical data like sales amounts and product IDs, while dimension tables store descriptive attributes such as product names and customer emails. Descriptive text attributes, hierarchies, and categories in dimension tables help arrange data into various hierarchies, allowing users to analyze and visualize data in different ways.
Relationships between tables are crucial for data modelling. A relationship is a rule that connects two or more tables, typically with a one-to-many relationship, where one row in the first table matches many rows in the second. Understanding the relationships between tables is key to creating accurate and efficient reports in Power BI.
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