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
How to recruit young employees into data management, explain the benefits of data governance, and create an information model to guide your architecture.
- By Lindsay Stares
- November 16, 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
The upcoming GDPR regulations require enterprises to consider three basic questions about their data. Here's how you can be ready with the answers.
- By Olivier Van Hoof
- November 14, 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
The recent data breaches should serve as a catalyst to more seriously consider what data we collect and store in our data warehouses.
- By Mike Schiff
- November 13, 2017
Are BI and self-service analytics headed inevitably toward more automation?
- By David Stodder
- November 10, 2017