Building a Data Lakehouse on Azure Data Lake Storage

Presented by

Ellie Vail, Product Manager, Azure Data Lake Storage, Microsoft, Tony Truong, Sr. Product Marketing Manager, Dremio

About this talk

In the rapidly evolving data landscape, organizations seek to use data assets to drive growth and competitive advantage. The problem is, the rigid warehouse-centric data architecture makes it hard to deliver faster access to data to end users without creating data copies and siloed ETL pipelines. As cloud data lakes grow, the challenge for many organizations will be providing access to that data for exploratory BI and interactive analytics. In this video, you will learn about building a data lakehouse on Azure Data Lake Storage with product leaders from Microsoft and Dremio: - The fundamentals of a data lakehouse architecture on Azure - The need for an open data lakehouse - Unifying data access on ADLS with Dremio - A self-service experience with Dremio and Power BI

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Dremio is the easy and open data lakehouse, providing self-service analytics with data warehouse functionality and data lake flexibility across all of your data. Dremio increases agility with a revolutionary data-as-code approach that enables Git-like data experimentation, version control, and governance.