Extract data for faster performance

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 extracting data works

When you extract data, you select an existing data source of any type, then select the specific fields you want to include in the extracted data source. You can apply filters and date ranges to reduce the amount of data even further. You can then use the extracted data source in your reports and explorations, just as you would a standard, live connection data source.

Extracted data and aggregation

Extracting data from an already aggregated data set, such as Google Ads or Analytics, creates a new, disaggregated data set. This makes performing  your own aggregation in extracted data sources more flexible than standard data sources. For example, in a standard Analytics data source, the Users metric is set to Auto aggregation, meaning you can't change it. In an extracted 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 using a standard (already aggregated) data source.

Create an extracted data source

1. Sign in to Looker Studio.
2. On the Looker Studio home page, in the top left, click Create, and then select Data Source.
3. In the connectors list, select Extract Data.
4. Select an existing data source to extract from.
5. Select the dimensions and metrics to extract by dragging them from the Available Fields list onto the targets, or by clicking Add. All the fields you add appear in the list on the far 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 range. Date ranges are required by some connectors, such as Analytics, but are optional for other connector types.
9. Give your data source a name by clicking Untitled Data Source in the upper left.
10. (Optional) To automatically refresh your data, in the lower right, turn on Auto update and set an update schedule.
11. In the lower right, click SAVE AND EXTRACT.

You can now add this data source to a report or exploration by clicking one of the buttons in the upper right.

Update extracted data

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

1. Sign in to Looker 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. (Optional) To automatically refresh your data, in the lower right, turn on Auto update and set an update 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 100 MB of data. If your extract contains more than 100 MB of data, Looker Studio will fail to extract and will display an error message.
• Extracted data sources contain static information: to refresh or update the data, turn on Auto update and set an update schedule.