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TDWI – Unlocking the Potential of Data Lakehouses: AI, Data Mesh, and Survey Insights, Part 2 of 2

More organizations are seeking a competitive edge by using technology such as AI to help them make more informed decisions, enhance operational efficiency, and drive innovation. As part of this evolution, enterprises are using high volumes of diverse data, resulting in a complex data landscape. Data professionals are taking greater interest in cloud data lakehouses as a solution for modern data management challenges. Data warehouses were designed for structured data, data lakes for managing large volumes of unstructured data. The lakehouse combines the scalability of data lakes and the reliability and performance of data warehouses.

At the same time, organizations are adopting new frameworks such as data mesh to overcome challenges posed by the complexity of modern AI data ecosystems. How are organizations utilizing data lakehouses for AI and how are they implementing a data mesh paradigm? In part two of this two-part series, Dremio’s CMO, Read Maloney, will share the results of the company’s survey of 500 organizations about AI, data mesh, and the data lakehouse. TDWI’s VP of Research, Fern Halper, Ph.D., will share TDWI research on the topic. They will discuss how organizations are using the lakehouse for AI and how data mesh helps enable scalability and agility and improve decision-making.

Watch and learn about:

  1. The current state of data lakehouse adoption
  2. How the data lakehouse is being used for AI
  3. Why and how organizations are implementing a data mesh framework to support AI on the lakehouse
  4. Best practices for getting started with AI and data mesh on the lakehouse
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