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MLOps.community
MLOps meetup #12 // Why Data Scientists Should Know Data Engineering with Dan Sullivan
May 21, 2020
59:51
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Explore why data scientists should know data engineering with Dan Sullivan, a software architect and data scientist. Learn about the advantages, challenges, and transitions in AI, MLOps, and cloud platforms. Discover the intersections of data roles, data warehouses, and data lakes in efficient data processing. Enhance data science efficiency and modeling through iterative feedback and skills in data engineering.
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Quick takeaways
- Data scientists benefit from learning data engineering skills for handling data at scale and improving productivity.
- Understanding the differences between data warehouses and data lakes optimizes data storage strategies.
Deep dives
Overview of Dan Sullivan's Background
Dan Sullivan is a software architect and data scientist with extensive experience in big data, machine learning, data architecture, security, stream processing, and cloud architecture. He has authored multiple LinkedIn learning courses and holds three PhDs in genetics, bioinformatics, and computational biology. Dan's prolific expertise brings a unique perspective to the discussion.
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