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Implementing Data Denormalization

In most cases, dimension tables should be denormalized. In this exercise, we'll use PySpark to load two dimension tables, products and categories, and denormalize the products table by replacing the categoryID column with the corresponding categoryName from the table categories.

Note: If you get an error about an API rate limit, this usually happens because a previous Fabric task has not completed. You can view active Fabric tasks from the Monitor page (located on the left vertical menu). Canceling old Fabric tasks in the Monitor page will usually resolve the rate limit error.

Cet exercice fait partie du cours

Transform and Analyze Data with Microsoft Fabric

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