Machine Learning Times
Machine Learning Times
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Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...
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10 years ago
The Great Analytical Divide: Data Scientist vs. Value Architect

 In the analytics space, it is quite common for many organizations to have a team of data miners who are now referred to as data scientists and a team of business users who are often referred to as value architects. It has been a common practice ever since the first direct marketing models were produced for the large catalog and publishing firms in the sixties that both the “data” person or data scientist and the “business” person or value architect needed to collaborate in developing a specific business solution. But the challenge then and the one that still

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