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Bridging the Gap: Integrating Data Science and Decision Science through Six Essential Questions

Towards AI

Many organizations have embraced the idea of having an analytic team in their structure. Yet, it is a little bit surprising to see that according to Gartner report estimated that: “ 60 percent of big data projects will fail to go beyond piloting and experimentation, and will be abandoned.”

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Customer Data Culture: The Innovators Have Already Reinvented Themselves

Alation

“We hear little about initiatives devoted to changing human attitudes and behaviors around data. Unless the focus shifts to these types of activities, we are likely to see the same problem areas in the future that we’ve observed year after year in this survey.” — Big Data and AI Executive Survey 2019. That’s no simple task.

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Announcing the ODSC East 2023 Keynote Speakers

ODSC - Open Data Science

Albert Vu CS Engineer, Taipy | Expert in Machine Learning and Big Data to Solve Optimization Problems Albert Vu’s focus is using machine learning and big data to solve (financial) optimization problems. He shares his expertise by developing projects of different skill levels for Taipy’s tutorial videos.

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Data Science Cheat Sheet for Business Leaders

Pickl AI

There are three main types, each serving a distinct purpose: Descriptive Analytics (Business Intelligence): This focuses on understanding what happened. Think of it as summarizing past data to answer questions like “Which products are selling best?” The Data Science Workflow Data science isn’t magic.