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You can optimize your extracts by only including the data you need. Specifically, you can exclude columns, create filters to limit the number of rows, aggregate data, and roll up dates.
Hidden fields are not included when you create an extract. By hiding unnecessary fields before you create an extract, you make the extract smaller and improve performance.
On the Data pane, click the drop-down arrow to the right of Dimensions and select Hide All Unused Fields from the context menu.
Right-click the data source and select Extract Data.
In the dialog box, optionally define one or more filters to limit how much data gets extracted.
Global filters are automatically added as filters on the extract.
After defining any filters, select Aggregate data for visible dimensions. This aggregates the data using the default aggregation for measures.
If the extract contains Date fields, you can also select Roll up dates to to adjust date granularity and further minimizing the size of the extract.
When ready, click Extract and specify a location for the extract (.hyper) file. The extract will only contain the visible fields and the data will be aggregated as you specified.
Refresh the extract at any time by selecting Data > Refresh All Extracts from the toolbar.