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June 10–13, 2024
San Francisco + Virtual
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Maximizing Value From Your Data with Lakehouse AI

Wednesday, June 28 @2:30 PM
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Ready to get started with lakehouses, especially around DS/ML? This session is for you.

The journey from training models to taking them to production can be quite challenging. Teams face a large variety of issues: siloed data, inconsistent tools, complex infrastructure, and a lack of visibility into their model performance. Learn how the Databricks Lakehouse Platform provides a unified, data-centric ML environment that accelerates and simplifies machine learning lifecycle, with a standardized set of tools, frameworks and governance used across your lakehouse data.

In this session, you’ll learn how about lakehouses, and how to:

  • Ingest, prepare and process data on a platform designed to handle production-scale ML training, including LLMs

  • Leverage data science notebooks and MLflow to manually train and track your ML experiments or let AutoML do the experimentation for you

  • Use real-time serving with fast autoscaling to save cost and maintain SLAs

  • Monitor your deployed models for drift and accuracy

  • Manage and govern all data and ML assets with Unity Catalog



  • Breakout


  • In Person, Virtual


  • DSML: Production ML / MLOps, Databricks Experience (DBX)


  • Intermediate


  • 40 min
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Session Speakers

Headshot of Craig Wiley

Craig Wiley

Sr. Director of Product, Lakehouse AI


Headshot of Jan Neumann

Jan Neumann

VP, Machine Learning


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