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The Data Decision-Maker’s Checklist For Improving ML/AI Operations With An End-To-End Lakehouse

The Data Decision-Maker’s Checklist For Improving ML/AI Operations With An End-To-End Lakehouse

Cloudera
Pages 4 Pages

Organizations can optimize ML/AI operations by adopting an end-to-end data lakehouse. Key steps include aligning lakehouse adoption with tech upgrades and business goals, breaking down data silos to boost productivity, taking a phased rollout to manage costs, and proving ROI with clear metrics. Benefits include accelerated time to value, better collaboration, improved governance, and reduced integration efforts, helping businesses unlock the full potential of their data assets.

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