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Table of contents
What is Aggregating in Tableau?
How to Implement Data Aggregation in Tableau?
Rules for Data Aggregation in Tableau
Implementing Various Aggregate Functions in Tableau
Frequently Asked Questions
Can I customise the aggregation level in Tableau?
What are the benefits of using Tableau for data aggregation?
Can I create my own custom aggregate functions in Tableau?
Last Updated: Mar 27, 2024

Aggregating Data Using Tableau

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Anubhav Sinha
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12 Jun, 2024 @ 01:30 PM


In today's data-driven world, organisations face the challenge of understanding complex data to gain valuable insights. Tableau, a popular data visualisation and business intelligence tool, offers a powerful solution for aggregating data. By summarising and combining information, Tableau helps users uncover hidden patterns and trends through easy-to-understand visuals. 

Aggregating Data Using Tableau

This article explores Aggregating Data Using Tableau using Tableau’s user-friendly interface and robust features. We will discuss aggregating data with Tableau, showcasing its ability to transform complexity into clear, actionable insights.

What is Aggregating in Tableau?

Aggregating Data Using Tableau involves calculations on data sets, enabling analysts to examine broad trends and patterns instead of specific data points. By aggregating data by categories, time periods, or locations, these functions provide a comprehensive perspective of the information. They summarise and consolidate data, uncovering significant insights that may not be apparent at an individual level. With the ability to analyse data at different levels of detail, such as by time or location, Tableau's aggregate functions empower analysts to simplify complex datasets and uncover valuable insights, driving informed decision-making.

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How to Implement Data Aggregation in Tableau?

Here are the implementation steps for Aggregating Data Using Tableau:

Step 1: Open Tableau and connect it to the data source you want to use.

data source selection

Step 2: Once connected, click on the "Sheet" tab at the bottom of the Tableau window.

sheet panel

Step 3: On the left side of Tableau, find the "Data" pane. Drag and drop the fields you want to analyse into the "Rows" and "Columns" sections of the worksheet.

data pane

Step 4: Apply aggregation functions to the fields. By default, Tableau uses the SUM function for numbers, but you can change it. Click the dropdown arrow near the field in the "Columns" or "Rows" section and choose the desired function (e.g., SUM, AVG, MIN, MAX, COUNT).

row panel

Step 5: If you want to group data based on specific criteria, drag additional fields into the "Rows" or "Columns" sections. Tableau will automatically group the data accordingly. You can also sort the data by right-clicking on a field and selecting the sorting options.

rows and columns panel

Step 6: You can customise the visual representation after aggregating and organising the data. Tableau provides options like bar charts, line charts, and pie charts. Choose the suitable visualisation type from the "Show Me" panel on the right side of the Tableau window.

show me panel

Step 7: Once you're done with data aggregation and visualisation, save your workbook by clicking on "File" and then "Save" or using the shortcut Ctrl + S. You can share the Tableau workbook with others by exporting it as a PDF or image, or by publishing it to Tableau Server or Tableau Public.

file options

Rules for Data Aggregation in Tableau

Here are some rules for Aggregating Data Using Tableau:

1. Use aggregation or apply level of detail (LOD) expressions for all fields in the "Columns" and "Rows" shelves.

2. Measures (numeric values) are aggregated by default, but you can change the aggregation function.

3. Dimensions are used for grouping data and are typically discrete fields.

4. Continuous fields are used for creating continuous axes, such as numerical scales.

5. Aggregate data at the appropriate level of detail for your analysis.

6. Choose the right aggregation function for summarising data (e.g., SUM, AVG, MIN, MAX, COUNT).

7. Handle NULL values using functions like IFNULL, ISNULL, or ZN.

Implementing Various Aggregate Functions in Tableau

Here’s the implementation of various aggregation functions in Tableau. For the dataset, we are using sample data from Tableau. When you open tableau desktop, you may find it under saved data sources: 

sample data sources


Calculates the total sum of a selected numerical field.

Syntax: SUM([Numerical Field])

SUM output


Calculates the mean value of a selected numerical field.

Syntax: AVG([Numerical Field])

AVERAGE output


Counts the number of records in a dataset.

Syntax: COUNT([Field])

COUNT output


Identifies the minimum and maximum value within a selected field.

Syntax: MIN([Field])


MIN and MAX output


Calculates the middle value in a dataset, dividing it into two equal halves.

Syntax: MEDIAN([Numerical Field])

MEDIAN output


Determines the number of unique values in a selected field.

Syntax: COUNTD([Field]) 



Calculates the standard deviation, measuring the variability or spread of values within a numerical field.

Syntax: STDEV([Numerical Field]) 


Frequently Asked Questions

Can I customise the aggregation level in Tableau?

In Tableau, you can customise how data is aggregated to fit your analysis needs. You have the flexibility to aggregate data at different levels of detail. It could be based on day, month, year, or any relevant dimension. 

What are the benefits of using Tableau for data aggregation?

Tableau's user-friendly design and versatile functions make data aggregation easier. Users can utilise it to find hidden patterns, make wise judgments, and visually compellingly share insights. Tableau's interactive dashboards and visualisations let users better comprehend data and effectively communicate results.

Can I create my own custom aggregate functions in Tableau?

Although Tableau has a large selection of built-in aggregate functions, users cannot design their own aggregate functions. Users can, however, take advantage of Tableau's adaptability by utilising calculated fields and sophisticated algorithms to derive bespoke measurements depending on their particular requirements.


In this article, we learned about Aggregating Data Using Tableau. We saw how to implement data aggregation in Tableau. We learned some rules for data aggregation. We also looked at the implementation of various aggregation functions in Tableau.

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