Organizations have been searching for optimal ways to store and analyze vast amounts of structured, unstructured, and semistructured data to handle the increasing volume, latency, resilience, and data-access requirements demanded by cross-functional teams. The lakehouse architecture, which combines the key benefits of data warehouses and data lakes, emerged to address some of these issues. In this session, learn how Google is extending the benefits of the lakehouse architecture into an end-to-end analytics lakehouse, enabling organizations to both extract data in real time – regardless of which cloud or datastore the data resides in – and to use it in aggregate for greater insight and AI with tools and features anchored on openness, choice, and simplicity.
Speakers: Irina Farooq
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