Extract Data functionality in Looker Studio can be used for more than just increasing report loading and refreshing speeds. In this lesson, we'll explore a few creative use cases for the Extract Data feature to optimize your reports further.
De-aggregation with Extract Data
One use case for Extract Data is de-aggregating auto-aggregated metrics, like revenue, transactions, and sessions from Google Analytics. Since Looker Studio doesn't have access to row-level data in a scorecard, de-aggregating these metrics can be challenging. By using Extract Data in Looker Studio, you can define breakdowns and extract row-level data to show average or maximum revenue per landing page, for example.
Keep in mind that extracting data using this method might cause a delay in the data, as extracts are only updated periodically. You can also use data blending in Looker Studio for de-aggregating metrics in real-time, although it might not be as fast as leveraging Extract Data.
Advantages and Considerations
Using Extract Data for de-aggregation offers several advantages:
Faster report loading times.
Access to row-level data for various statistical calculations, such as count, minimum, maximum, standard deviation, and variance.
However, it's essential to understand that using Extract Data for de-aggregation may result in a delay of data, as updates can be up to a day late.
Extract Data in Looker Studio offers creative ways to optimize your reports beyond just improving loading speeds. For example, using this feature allows for de-aggregating auto-aggregated metrics from Google Analytics, providing more in-depth insights and calculations.
Remember the advantages and considerations when using Extract Data for these additional use cases to ensure a balance between optimal performance and data timeliness. Always consider the specific requirements of your reports before leveraging Extract Data for creative uses.
