Aggregation, Granularity, & Level of Detail | Tableau Course Tutorial For Beginners | @henryharvin

Aggregation, Granularity, & Level of Detail | Tableau Course Tutorial For Beginners | Henry Harvin

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This Henry Harvin video on “Aggregation, Granularity, & Level of Detail ” is a complete Aggregation, Granularity, & Level of Detail tutorial for beginners who want to learn Aggregation, Granularity, & Level of Detail. Here you learn all about Aggregation, Granularity, & Level of Detail .
Aggregation and granularity are complementary concepts. Aggregation is a mathematical operation that takes multiple values and returns a single value: operations like sum, average, count, or minimum. This changes the data to a lower granularity (aka a higher level of detail)
When Aggregate Measures is selected, Tableau will attempt to aggregate measures in the view by default. This means that it collects individual row values from your data source into a single value (which becomes a single mark) adjusted to the level of detail in your view.
Granularity refers to the level of detail of the data stored in a table or in other words. ”What does a single row in a data table represent?” Tableau Tip: The term 'Level of Detail' (which you may have come across in many Tableau Blogs, and Articles.
Level of Detail (LOD) expressions are used to run complex queries involving many dimensions at the data source level instead of bringing all the data to Tableau interface. A simple example is adding dimension to an already calculated aggregate value.

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