Subject archive for "managing-data-science"


Rocketing Confidence in Data Science, Poll Finds: Are Better Tools the Reason?

Businesses are increasingly betting big on data science for ambitious near-term growth, just one more indication that the rapidly rising profession is making itself a huge force for innovation in fields as diverse as healthcare & pharma, defense, insurance, and financial services. Nearly half of respondents in a recent poll said that their company’s leadership expects data science efforts to produce double-digit revenue growth. A similar survey in 2021 put that same figure at only 25%, indicating growing expectations for the young profession.

By Lisa Stapleton4 min read

Data Science

What is the Data Science Lifecycle for Data Science Projects?

Data science is an incredibly complex field. When you factor in the requirements of a business-critical machine learning model in a working enterprise environment, the old cat-herding meme won’t even get a smile.

By David Weedmark12 min read

Data Science

Why models fail to deliver value and what you can do about it.

Building models requires a lot of time and effort. Data scientists can spend weeks just trying to find, capture and transform data into decent features for models, not to mention many cycles of training, tuning, and tweaking models so they’re performant.

By David Bloch9 min read

Data Science

Themes and Conferences per Pacoid, Episode 12

Paco Nathan's latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams.

By Paco Nathan31 min read

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