Subject archive for "data-engineering," page 2

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise.

In this guest post, Holden Karau, Apache Spark Committer, provides insights on how to create multi-language pipelines with Apache Spark and avoid rewriting spaCy into Java. She has already written a complementary blog post on using spaCy to process text data for Domino. Karau is a Developer Advocate at Google as well as a co-author on High Performance Spark and Learning Spark. She also has a repository of her talks, code reviews, and code sessions on Twitch and Youtube.

This blog post provides highlights and a full written transcript from the panel, “Data Science Versus Engineering: Does It Really Have To Be This Way?” with Amy Heineike, Paco Nathan, and Pete Warden at Domino HQ. Topics discussed include the current state of collaboration around building and deploying models, tension points that potentially arise, as well as practical advice on how to address these tension points.

This blog post provides highlights and a full written transcript from the panel, “Data Science Versus Engineering: Does It Really Have To Be This Way?” with Amy Heineike, Paco Nathan, and Pete Warden at Domino HQ. Topics discussed include the current state of collaboration around building and deploying models, tension points that potentially arise, as well as practical advice on how to address these tension points.

This blog post includes candid insights about addressing tension points that arise when people collaborate on developing and deploying models. Domino’s Head of Content sat down with Don Miner and Marshall Presser to discuss the state of collaboration between data science and data engineering. The blog post provides distilled insights, audio clips, excerpted quotes as well as the full audio and written transcript. Additional content on this topic will be forthcoming from additional industry experts.

Introduction: New Monthly Series!