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RESEARCH & RESOURCES

Available On-Demand - This webinar has been recorded and is now available for download.

Maximizing the Value of Your Data Lakehouse: How to Leverage a Data Catalog for Success

Webinar Speaker: Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics

Date: Thursday, May 2 2024

Time: 9:00 a.m. PT / 12:00 p.m. ET

As part of their strategy to become more competitive, many organizations are collecting high volumes of diverse data for data science initiatives. To support this, they are moving to cloud data platforms, such as the data lakehouse, that can support both structured and unstructured data types. The data lakehouse is a combination of a data lake and a data warehouse that provides warehouse data structures and data management functions on low-cost platforms, such as cloud object store. At TDWI, we’re seeing growing use of the lakehouse architecture.

In order to support the migration to the lakehouse as well as maximize the value of the data in the lakehouse for data science, organizations are making use of the data catalog. The data catalog can help identify and prioritize which data sets are the most critical to move first. It also facilitates data discovery, enables users to share and collaborate on data assets, and supports data governance.

Join this TDWI webinar to learn more about how the data lakehouse and the data catalog can help organizations succeed with analytics. Topics include:

  • Why organizations are moving to the lakehouse architecture
  • Making the move to the lakehouse: how the data catalog can help
  • Using the data catalog for discovery and collaboration for data science on the lakehouse
  • Best practices for getting started

Guest Speakers

Todd Beauchene
Director of Partner Integrations
Alation

Raja Perumal
Senior Alliances Manager
Hybrid Data Services & AI
Databricks

Raja Perumal is a senior alliances manager at Databricks, focused on data governance ISVs. He has spent 10 years in analytics consulting helping organizations deal with large amounts of data before working at Alation and Snowflake.

Fern Halper, Ph.D.


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