It’s more complicated than you think. Let me explain.

In my first sample data set I have just the two columns of data below and 365 rows, one for each day of 2018.

I want to consolidate this data so I just have one row for each month. To do this, I create an extract and aggregate at the month level:

With this approach, the result is 12 rows of data.

Let’s add a wrinkle.

In my second example data set I added a Region field. I now have 730 rows of data, one for each day and each region in the data set (there are only two regions, East and West).

Now when I extract and aggregate at the month level the result is 24 rows of data.

You might be wondering, “What rule is Tableau is applying?”.

Tableau will aggregate the data at a month level, but it will create a unique row of data for every possible combination of dimensions as well. If you have a lot of dimensions in your data set, aggregating at the month level might not consolidate your data much.

If you have 1000s of rows of data and just want to aggregate at a specific dimension level, consider using the Tableau Prep Aggregate Function which gives you total control over what level an aggregation occurs.

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