Creating a Data Extract with Tableau Desktop

Task: There are several reasons that Tableau Data Extracts (TDEs) are essential to Tableau users and why we strongly suggest that USNH Tableau Developers use extracts when publishing to server but performance is the most important reason. Beyond performance, an added benefit to extracts is the ability to automate updates from scheduled WebI reports. 
  • Performance: Data extraction offers increased performance when the underlying data source is slow.
    Reduced load: Replacing a live connection to an OLTP database—or any database—with a TDE reduces the load on the database that can result from heavy Tableau user traffic.
  • Portability: A TDE can be bundled with Tableau visualizations in a packaged workbook for easy sharing and collaboration.
  • Pre-aggregations: Tableau gives you the option to aggregate your data for all visible dimensions when creating the Extract. This is known as an aggregated extract. An aggregated extract is smaller and contains only aggregated data, as the name implies—not all of the row-level data that is stored in a standard TDE. Accessing the values for additive aggregations in a visualization becomes near-instantaneous because all of the work to derive the values has already been done. So, the most basic reason to use an aggregated extract is performance.
  • Materialization of calculated fields: When you optimize a Tableau extract, all of the calculated fields that have been defined are converted to static values upon the next full refresh. At that point, they essentially become additional data fields that can be accessed and aggregated as quickly as any other field in the TDE. The increase in performance can be especially strong when working with string calculations as string calculations are significantly slower than numeric and/or date calculations. So, as was the case with aggregated extracts, the most basic reason to optimize a TDE is again performance.
  • Publishing to Tableau Public and Tableau Online: Tableau Public only supports TDEs. While Tableau Online can connect live to cloud-based data sources, TDEs are the most common data source used in that environment.


Though there are a number of places in your Tableau workflow where you can create an extract, the primary method is described below.

1. After you connect to your data and set up the data source on the Data Source page, in the upper-right corner, select Extract, and then click the Edit link to open the Extract Data dialog box.

Extract option found in the upper right corner of the Data Source Page

2. (Optional) Do one or more of the following to define filters and limit the amount of data in your extract:

a. Click Add to define one or more filters to limit how much data gets extracted based on fields and their values.
b. Select Aggregate data for visible dimensions to aggregate the measures using their default aggregation. Aggregating the data consolidates rows, can minimize the size of the extract file, and increase performance. When you choose to aggregate the data, you can also select Roll up dates to a specified date level such as Year, Month, etc. The examples below show how the data will be extracted for each aggregation option you can choose.

Aggregation examples image
c. Select the number of rows you want to extract. You can extract All rows or the TopN rows. Tableau first applies any filters and aggregation and then extracts the number of rows from the filtered and aggregated results. The number of rows options depend on the type of data source you are extracting from.

Edit extract dialog box used to define filters that limit the data that gets extracted

3. When finished, click OK.

4. Click the sheet tab. Clicking the sheet tab initiates the creation of the extract.

Sheet tab located in the bottom left corner of the desktop tool

5. In the dialog box, select a location to save the extract, give the extracted file a name, and then click Save.


Users should be able to create a Data Extract using Tableau.

Further reading:

For more information see Tableau 2019.1 - Creating a Data Extract with Box Connector.

Read more from Tableau about extracts.

Need additional help?

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Article ID: 1629
Fri 7/19/19 6:14 PM
Thu 5/19/22 2:21 PM