BigQuery provides petabyte-scale data warehousing with consistently high performance for all users. However, users coming from traditional enterprise data warehousing platforms often have questions about how best to adapt their workloads for BigQuery. Chad Jennings explores best practices and integration with BigQuery with special emphasis on loading and transforming data for BigQuery, as well as how BigQuery integrates with the rest of the Google Cloud Platform—including Apache Spark on Google Cloud Dataproc. Chad also discusses Big Query’s SQL dialect and its ability to handle the industry’s most common queries.
This session is sponsored by Google.
Chad W. Jennings is a product manager for BigQuery at Google Cloud. Chad has a long history in navigation processing; he came to Google from the startup world, where he worked on navigation algorithms on airplanes, helicopters, and mobile phones, and holds a PhD in aeronautics and astronautics from Stanford University. He is an avid skier and surfer. When he’s not working on big things or playing in nature, he’s at home with his wife and two young children.
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