Palo Alto Networks Launches NextWave 3.0 to Help Partners Build Expertise in Dynamic, High-Growth Security Markets
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Registration: 2/25 – Saviynt Enterprise IGA for M365 (US/EMEA)
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Business analysts working with larger and larger data sets are finding traditional BI methods can’t keep up with their need for speed. BigQuery BI Engine is designed to meet this need by accelerating the most popular dashboards and reports that connect to BigQuery. With the freshest data available, your analysts can identify trends faster, reduce risk, match the pace of customer demand, even improve operational efficiency in an ever-changing business climate.
Today, we are excited to announce that we are extending BigQuery BI Engine to work with any BI or custom dashboarding applications that require sub-second query response times. In this preview, BI Engine will work seamlessly with Looker and other popular BI tools such as Tableau and Power BI without requiring any change to the BI tools.
“Our business users are hungry for data and expect a lot from our team, so as soon as we had the opportunity to turn on BI Engine for BigQuery and Looker, we did and the performance-matched to the speed of business expectations and greatly improved the load times for dashboards,” said Harish Ramachandraiah, Director of Engineering and Analytics at Sunrun.
This fast in-memory analysis service allowed the marketing, sales, and operations business users to analyze large and complex datasets interactively in Looker and Data Studio.
“It helped the development team too, with its simplified architecture for getting started quickly without managing complex, post-ETL transformations and data pipelines. We saw 40% performance increases and we have 1000+ users interacting with the data daily via Looker and Data Studio, so this was a very effective way to improve their data experiences, save them time, and positively impact the data culture at Sunrun,” said Kiran Manne, Architect on the BI team at Sunrun.
BI Engine is now natively integrated into the BigQuery API. Users of any BI tool or custom applications that connect to BigQuery API via JDBC/ODBC, can now take advantage of BI Engine by reserving BI Engine capacity in their GCP projects and specifying the size of memory.
Architecturally, we revamped BI Engine with a distributed in-memory execution engine for always-fast experiences. BI Engine utilizes modern techniques such as vectorized processing, advanced data encodings, adaptive caching and query plans tuned for in-memory execution. When queries exceed the size of a reservation, BI Engine seamlessly adapts into a mixed mode operation by using BigQuery Slots.
