Organizations are looking to streamline their data management by melding their data warehouse and data lake into a single data lakehouse. A lakehouse provides a highly performant and reliable single source of data at a lower cost. See how DoorDash and Grammarly have used the Databricks Lakehouse Platform on AWS to:

  • Address multiple data science use cases — including recommendation models, logistics and demand forecasting — as well as fraud detection
  • Enable their business analysts to access dashboards to view business performance and address issues immediately
  • Have a single automated system to manage their data pipelines to support these use cases and more

In this webinar, you’ll learn how a lakehouse:

  • Speeds GTM iteration and enables a more productive, efficient ML team, resulting in increased revenue and profitability
  • Provides a scalable, predictable framework, minimizing risk and lowering TCO by alleviating unnecessary DevOps

This session will also include a demonstration of how you can get started and a live Q&A.

Speakers

  • Hien Luu, Head of Machine Learning Platform, DoorDash
  • Michael Keba, Data Engineer, Grammarly
  • Franco Patano, Sr. Solutions Architect, Databricks

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