A data analyst regularly creates interactive reports in Looker Studio based on multi-terabyte datasets stored in Google BigQuery. The dashboard users report slow chart loading times, and the organization wants to accelerate query response times using an in-memory caching mechanism while minimizing BigQuery query computation costs. Which service should be configured to optimize Looker Studio dashboard performance with BigQuery?

BigQuery BI Engine: ### **What BigQuery BI Engine is:** **BigQuery BI Engine** is a fast, in-memory analysis service built directly into Google BigQuery. It enables business intelligence (BI) and visualization tools—such as **Looker Studio**, **Looker**, and third-party BI applications—to interactively query large datasets with sub-second response times and high concurrency. ### **How it meets the requirements:** - **Accelerates dashboard performance (✓):** BI Engine caches frequently queried data and analytical structures in memory, allowing Looker Studio charts and tables to refresh almost instantaneously without waiting for standard disk-based query execution. - **Reduces query compute costs (✓):** Because queries hitting the BI Engine in-memory cache do not scan raw storage for each visualization reload or filter change, organizations reduce on-demand slot consumption and scan-based query costs. - **Native Looker Studio integration (✓):** Looker Studio automatically detects and routes compatible queries directly through BigQuery BI Engine without requiring complex pipeline re-architecting or manual ETL data extract steps. ### **Key advantages and capabilities:** - **Sub-second latency:** Delivers millisecond-to-second query response times for interactive user filtering, sorting, and drill-downs. - **Zero ETL required:** Works directly on top of existing BigQuery tables, views, and partitioned datasets without needing custom aggregation pipelines. - **Seamless autoscaling:** Intelligently allocates and caches query plans and data columns based on user interaction patterns. - **Direct console enablement:** Administrators can provision BI Engine reservation capacity directly within the Google Cloud console for designated projects and regions. ### **Why this is optimal:** BigQuery BI Engine is purpose-built to sit between BigQuery storage and visualization tools like Looker Studio. It provides an immediate speed and cost optimization layer specifically designed for analytical dashboard workflows.