Databricks, founded by the original creators of Apache Spark™ and Delta Lake, is thrilled to be a Platinum sponsor at AWS re:Invent 2020, where you can see how we simplify data engineering, analytics and ML with a unified platform. This year, we are bringing the magic and intrigue to your living room. We’ve got a surprise in store – a private online show with David Blaine the master illusionist. He makes the extraordinary look simple — just like Databricks. Sign up now to secure your spot! The show will take place on Monday, December 14 at 5:00 PM PST.
In our session, “Stop Struggling with Analytics on the Data Lake” you will hear from Denis Dubeau, Partner Solution Architect about how Comcast and Digital Turbine are simplifying data engineering, analytics and ML with the Databricks Unified Data Analytics Platform. The session will air in three different time zones on December 17. Learn how to use Databricks, with Delta Lake, to make the data in your S3 data lake reliable with higher performance, so it can support all your analytics across data science, machine learning and BI/reporting. Companies like Comcast have used this approach to reduce costs by $9 million and improve model deployment from weeks to minutes!
|Log into the re:Invent Databricks booth to check out the four demos available at the conference. Ask our data and AI experts questions live at the booth for any questions about these demos or your own projects.|
Delta Lake and AWS Glue – see how Delta Lake, as a managed service on Databricks, is integrated with AWS Glue as a metadata store.
SQL Analytics – see the new SQL Analytics service Databricks announced at Data + AI Summit, enabling your SQL analysts to analyze your entire data lake.
AWS Quickstarts: Databricks – Databricks is available as an AWS Quickstarts, which provides a pre-configured guide to get you up and running with Databricks in no time.
MLflow and AWS SageMaker – see how MLflow and AWS SageMaker are integrated to provide a seamless way to manage your machine learning operations and distribute your models.
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