3.9. Caching & Data Freshness

3.9. Data Freshness & Caching in Looker Studio

In the data source interface, we can adjust the data freshness threshold of each data source we have for caching data and fetching data from cache.

Caching in Looker Studio

Looker Studio has caching capabilities to ensure faster data retrieval. Each data source has a data freshness setting, which determines how often data is fetched from the source.

The default setting is usually 12 hours, but you can adjust it to one hour, four hours, or even one to 15 minutes for BigQuery. Each data source can have a unique caching and data fetching setting.

How Caching Works

When a report loads, Looker Studio tries to extract fresh data if it's outside the data freshness threshold. However, if the data requested is the same as previously cached data and within the data freshness window, Looker Studio will use the cached data instead.

For example, if you refresh a report multiple times within the 12-hour window without changing any settings, Looker Studio won't repeatedly request fresh data. But once the data freshness threshold is passed, it will fetch new data, even if the same data is being requested.

Note: If you change any setting in the data requested (date range, segment, filter set, or fields), Looker Studio will need to fetch new data regardless of the data freshness setting.

Identifying Cached Data

When a report is powered by cached data within the data freshness setting, you'll see a lightning bolt icon. This icon indicates the last time fresh data was received from the data source. If the icon isn't present, it means the data was requested live from the underlying data source.

Understanding data freshness and caching in Looker Studio helps you manage your data efficiently, ensuring your visualizations are both up-to-date and fast-loading.