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May 17 Webinar: Data Warehouse or Data Lake, Which Do I Choose?

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DATE: May 17, 2022, This webinar has passed. The recording will be made available On Demand within the next two US business days.

TIME: 2 PM Eastern / 11 AM Pacific

PRICE: Free to all attendees

This webinar is sponsored by:

About the Webinar

Today’s data-driven companies have a choice to make – where do we store our data? As the move to the cloud continues to be a driving factor, the choice becomes either the data warehouse (Snowflake et al) or the data lake (AWS S3 et al). There are pro’s and con’s for each approach. While the data warehouse will give you strong data management with analytics, they don’t do well with semi-structured and unstructured data with tightly coupled storage and compute, not to mention expensive vendor lock-in. On the other hand, data lakes allow you to store all kinds of data and are extremely affordable, but they’re only meant for storage and by themselves provide no direct value to an organization.

Enter the Open Data Lakehouse, the next evolution of the data stack that gives you the openness and flexibility of the data lake with the key aspects of the data warehouse like management and transaction support.

In this webinar, you’ll hear from Ali LeClerc who will discuss the data landscape and why many companies are moving to an open data lakehouse. Ali will share more perspective on how you should think about what fits best based on your use case and workloads, and how some real world customers are using Presto, a SQL query engine, to bring analytics to the data lakehouse.

About the Speaker

Ali LeClerc 

Head of Community, Ahana

Ali has over a decade of experience in open source software, product, and community marketing. She’s currently the Head of Community at Ahana, the SaaS for Presto company, where she works closely with the Presto Foundation to drive open source programs. Prior to Ahana, Ali held community and marketing positions at Alluxio, Couchbase, and Time Warner. She holds a degree from Yale University in Political Science.

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