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Tableau - Level Of Details

Updated: Mar 13

Author: Shashank Sanehi

What are LOD's:

LOD stands for Level Of Detail

This allows us to control the granularity and the level of detail of your expression.

As the name suggests, it tells us that we can view or modify data at different levels. It can be an overview, high level, or more specific ( low level).

In Tableau, we have three types of LODs i.e

  1. FIXED



The hierarchy of these LODs is shown in the picture below.

fig 1

Syntax of LOD -

The dimension field is optional while writing. Therefore we can also write:

{FIXED : SUM([User Fans])}

Now we will see each LOD's one by one.


We can infer meaning from the name fixed, as it means constant or something which can't be changed.

Therefore, FIXED LODs are used when we don't want to change a particular value.

The result of The FIXED LOD is scalar.

It is also not affected by dimension filters and every filter which comes below it, as seen in fig 1.

Let's look at an example from our sample superstore data source.

In fig 2 below, we are finding the sum of sales based on category and have written a FIXED LOD expression. As it is not affected by dimension filters, we will try to change the dimensions and uncheck a few categories and see the difference.


fig 2

fig 3

As we can see, we have changed and unchecked a few category filters. There is no effect on the FIXED LOD grand total.

But if we want to change the values without using context filters, every time, we can make use of EXCLUDE.


As the name says, it means we are not considering a part or excluding a part from the total in our case dimension.

Therefore, if we change the dimension filters, it will affect the results as EXCLUDE is affected by dimension filters, as shown in fig 1.

The result of an EXCLUDE is ATTR.

Let's use the same example as we used in the FIXED LOD.

{ EXCLUDE [Category]: SUM([Sales])}

We are again changing the dimensions and unchecking the furniture. Let's see the difference.

fig 4

The values are changed as we make changes in the category dimension.

fig 5

As the name suggests, we are including or adding something to get deeper insights from our data.

For example, if we want to know the average profit by region but don't want to show the region in our viz, we can use INCLUDE LOD

AVG({ INCLUDE [Region]: SUM([Profit])})

As we want an average profit, we are writing the included expression inside an average aggregate calculation, as shown in fig 6

fig 6

And now, we can use the LOD on another sheet, as shown in fig 7, without showing the region.

fig 7

We have used the included LOD to show a region-wise average profit on a map without showing the region, as shown in fig 7.


We have seen how Various LODs are used in Tableau.


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