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Basics of understanding level of details (LODs) in Tableau

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Dimensions and measures

Why is it important to understand dimensions and measures?

Understanding dimensions and measures are not specific to LOD calculations but a fundamental aspect required to learn Tableau and data in general.

Dimensions are discrete columns of data, usually names but can also be numerical. In Tableau, they are represented by blue pills (picture).

Measures are continuous columns of data, usually numbers. In Tableau, measures are represented by a green pill (picture)

Granularity of data

The granularity of data is the amount of information within each row. The columns that make each row unique in your table can be used to determine your level of detail. This makes understanding your granularity of data critical in effectively using LOD calculations.

Level of detail

In Tableau, there is a view/window that contains your Level of Detail. The level of detail is determined by the dimensions contained in the row and column shelves.

The dimensions you use can have a hierarchical structure in the table

Aggregation/calculations in Tableau

What are aggregations in Tableau?

Aggregations are actions that Tableau performs to manipulate data. These actions can be but are not limited to summation, averages, and count.

How are aggregations/calculations performed in Tableau?

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