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The Databricks Lakehouse Platform

Enterprises today struggle with the complexity of maintaining both data lakes and data warehouses. They grapple with data silos that prevent a single source of truth, the expense of maintaining complicated data pipelines, and reduced decision-making speed.

Hear from Databricks Co-founder and CEO Ali Ghodsi as he discusses why data warehouses and data lakes weren’t designed for today’s use cases, and how the lakehouse builds on these technologies to better unlock the potential of your data. This new, simplified architecture allows traditional analytics and data science to coexist in the same system.

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Customer use case: Building the lakehouse at Atlassian

Session Duration: 12 minutes

Rohan Dhupelia of Atlassian talks about the evolution of their internal data architecture to the lakehouse as the “sweet spot” in between the data warehouse and data lake.

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Training: How to build a lakehouse

Session Duration: 120 minutes

Join our How to Build a Lakehouse technical training, where we’ll explore how to use Apache SparkTM, Delta Lake, and other open source technologies to build a better lakehouse. This virtual session will include concepts, architectures and demos.

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Data Management: The Good, The Bad, The Ugly

Session Duration: 50 minutes

Learn how Databricks helps data engineers sleep at night by simplifying data management — from data processing with ETL to data governance — and why that makes the lakehouse architecture a reality.

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