Databricks at AWS re:Invent
The world’s first lakehouse — simple, open and multicloud
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A data lakehouse unifies the best of data warehouses and data lakes in one simple platform to handle all your data, analytics and AI use cases. It’s built on an open and reliable data foundation that efficiently handles all data types and applies one common security and governance approach across all your data and cloud platforms.
Explore lakehouse at these sessions:
Tuesday, November 29 | 5-6 PM PT | Encore – Encore Ballroom 5
Thermo Fisher Scientific empowers customers to make the world healthier, cleaner and safer. Converting raw, streaming data into comprehensive views for fast and accurate decisions requires a simple, open and efficient data architecture. Learn how Thermo Fisher Scientific built a data lakehouse using the Databricks Lakehouse Platform on AWS to address challenges across data engineering, streaming analytics, model development and delivery.
Wednesday, November 30 | 4-5 PM PT | Wynn — Bollinger
Computer vision technologies help manufacturers automate product quality control, saving time and reducing waste. Corning has accelerated product delivery and reduced costs by using image recognition with a complete, end-to-end machine learning lifecycle built on the Databricks Lakehouse Platform. Learn how Corning automated product quality checks to minimize manual inspections, lower shipping costs and increase customer satisfaction.
Party at the Lakehouse
Join Databricks, Deloitte and dbt Labs at Topgolf for a party at the lakehouse. Golfing, games and prizes, and a chance to meet and network with some of the brightest minds in data, analytics and AI.
Meet 1:1 at the Lakehouse
Connect with our data, analytics and AI experts to discuss your data challenges and find out how we can help you resolve them. Come learn how your data pipelines can be automated to handle streaming and batch data, automatically refining and improving the data to make it available to data scientists and data analysts. Discover how you and your team can collaborate in real time to author data science, data engineering and machine learning notebooks, using Python, SQL, R and Scala. Learn how you can build a lakehouse that can handle all your data and analytics use cases.