What leaders need to understand about building a data science program, embracing a shift in IT’s role, and preparing for next year.
- By Lindsay Stares
- November 30, 2017
At this year's Teradata Partners conference, two central themes point to significant trends.
- By William McKnight
- November 28, 2017
Can artificial intelligence keep enterprise data safe and stay ahead of hackers' latest techniques?
- By Brian J. Dooley
- November 21, 2017
Why there are few entry-level jobs in data science, how vendors say machine learning will cleanse data, and which statistical techniques are most important in data science.
- By Lindsay Stares
- November 21, 2017
Creating a compelling business case is a greater challenge than building the edgiest of algorithms.
- By Jill Dyché
- November 20, 2017
Artificial intelligence, blockchain, and the Internet of Things have brought major, sometimes unwelcome shifts within the finance industry.
- By Michael Volkmann
- November 17, 2017
A quick look at how five vendors have embedded machine learning, NLP, or other advanced analytics technologies into their platforms.
- By Fern Halper
- November 15, 2017
Codifying the definition of a data scientist, training data science skills in-house, and projecting the rise and fall of demand.
- By Lindsay Stares
- November 14, 2017