Extract data for faster performance

Improve the performance of reports and explorations by extracting data from your data set.

Data extract lets you explore a subset of your data. This can make your reports and explorations load faster and be more responsive when applying filters and date ranges than when working with a live connection to your data.

How data extract works

Extracting data into Data Studio creates an extracted data source. Extracted data sources can contain a subset of the fields and records from your original data set. You add the extracted data source to your reports and explorations, just as you would with a standard, live connection data source.

To extract data

You can create extracted data sources in the Explorer, or directly through the Data Sources tool:

In the Explorer

  1. Sign in to Data Studio.
  2. In the top left, click Create, then select Explorer.
  3. Select an existing data source or create a new one.
  4. In the DATA properties panel on the right, under the data source name, click Create new object. EXTRACT DATA.
  5. In the left-hand panel, select the dimensions and metrics to extract. These will appear in the list on the right.
  6. (Optional) If the data is unaggregated, consider applying an aggregation, such as Sum, or Average, to reduce the amount of data extracted.
  7. (Optional) Apply filters to the data in order to reduce the number of rows.
  8. Apply a date filter. Date filters are required on some connectors, such as Analytics, but are optional for other connector types.
  9. The default name for your data source is "Extracted Data Source." You can change this using the field in the upper right panel.
  10. (Optional) To automatically refresh your data, enable “Auto update” and select an update schedule.
  11. In the lower right, click SAVE AND EXTRACT.

In the Data Sources tool

  1. Sign in to Data Studio.
  2. In the top left, click Create, then select Data Source..
  3. Select Extract Data.
  4. In the left-hand panel, select the dimensions and metrics to extract. These will appear in the list on the right.
  5. (Optional) If the data is unaggregated, consider applying an aggregation, such as Sum, or Average, to reduce the amount of data extracted.
  6. (Optional) Apply filters to the data in order to reduce the number of rows.
  7. Apply a date filter. Date filters are required on some connectors, such as Analytics, but are optional for other connector types.
  8. The default name for your data source is "Extracted Data Source." You can change this using the field in the upper right panel.
  9. (Optional) To automatically refresh your data, enable “Auto update” and select an update schedule.
  10. In the lower right, click SAVE AND EXTRACT.

Update extracted data

To update the information contained in a data extract, enable “Auto update” or edit the data source connection and extract the data again:

  1. Sign in to Data Studio.
  2. Navigate to the DATA SOURCES Home page.
  3. Locate the extracted data source.
  4. Click the data source to edit it.
  5. In the upper left, click EDIT CONNECTION. You must be the data source owner to see this option.
  6. Enable “Auto Update” and select a refresh schedule. 

  7. In the lower right, click SAVE AND EXTRACT.

Delete your extracted data

Deleting an extracted data source also deletes its data from Google servers.

Limits of data extract

  • Extracted data sources can contain up to 100MB of data.
  • Extracted data sources contain static information: to refresh or update the data, enable Auto Update and set a refresh schedule. 
  • Field aggregation in extracted data sources can be more flexible than standard data sources. For example, in a standard Google Analytics data source, the Users metric is set to Auto aggregation, meaning you can't change it. In an extracted Google Analytics data source, you are free to apply any of the available aggregation types. This can help you explore different interpretations of your data than is possible in reports.
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