A retail enterprise maintains a central BigQuery table containing precalculated hourly sales performance metrics. A Looker Studio executive dashboard connected to this dataset is accessed frequently by hundreds of regional managers throughout the business day. The underlying data pipeline updates the BigQuery precalculated table every hour on the hour. You need to configure the Looker Studio data source connection to minimize BigQuery query costs and visualization latency while strictly honoring the 1-hour reporting freshness SLA. How should you configure the data source connection in Looker Studio?

Configure the data source to use Owner's Credentials and set the data freshness threshold to 1 hour.: ### What the solution is Configuring a Looker Studio data source with **Owner's Credentials** and setting a **1-hour data freshness threshold** optimizes cached query reuse across all dashboard consumers while aligning cache invalidation with the underlying hourly ingestion pipeline. ### How it meets the requirements - **Minimizes query costs and latency:** When a data source uses **Owner's Credentials**, Looker Studio shares cached query results in memory across all viewers. When hundreds of regional managers access identical reports or precalculated summary cards, queries are served directly from Looker Studio's in-memory cache rather than issuing redundant, billable SQL queries against BigQuery. - **Honors the 1-hour freshness SLA:** Aligning the data freshness interval to **1 hour** ensures that once the hourly threshold elapses, Looker Studio clears expired cache entries and fetches the newly updated precalculated dataset from BigQuery on the next query, ensuring no user sees data older than 60 minutes. ### Key advantages - **Shared memory cache:** A single cached result set serves hundreds of simultaneous viewers, drastically reducing compute scan volume. - **Predictable cost footprint:** Reduces recurring BigQuery on-demand analysis fees and slot contention. - **Sub-second render speeds:** Eliminates round-trip database queries for repeat tile views across different users. - **Automated invalidation:** Avoids requiring manual dashboard refreshes from users. ### Why this is optimal This approach directly balances performance, storage, and freshness SLAs by pairing centralized cache management (via Owner's Credentials) with scheduled pipeline cadence (1-hour cache eviction).