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Successful AI_ML Projects with End-to-End Cloud Data Engineering
Successful AI_ML Projects with End-to-End Cloud Data Engineering

Successful AI_ML Projects with End-to-End Cloud Data Engineering

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Trusted, high-quality data and efficient use of data engineers’ time are critical success factors for AI/ML projects. Enterprise data is complex—it comes from several sources, in a variety of formats, and at varied speeds. For your machine learning projects on Apache Spark, you need a holistic approach to data engineering: finding & discovering, ingesting & integrating, server-less processing at scale, and data governance. Stop by this session for an overview on how to set up AI/ML projects for success while Informatica takes the heavy lifting out of your data engineering.

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