Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Jev Fever: Predictive AI Is Superhot Again
  Originally published in Forbes The more AI changes, the...
GenAI Owns the Hype, but Predictive AI Is Thriving
  EDITOR’S NOTE: This article is adapted from the...
The Data Disconnect: A Key Challenge for Machine Learning Deployment
  EDITOR’S NOTE: This article is excerpted from The...
A Brief History of Why Machine Learning Projects Stall
  EDITOR’S NOTE: This is the preface to The...
SHARE THIS:

13 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

This content is restricted to site members. If you are an existing user, please log in on the right (desktop) or below (mobile). If not, register today and gain free access to original content and industry news. See the details here.

Comments are closed.