Business people have been going around IT organizations for about as long as they've been dealing with them. In a recent report, Gartner tackles the emerging problem of going around IT for analytics.
Three things that distinguish data prep from the traditional extract, transform, and load process.
- By Wei Zheng
- February 10, 2017
Strategies for quality data science investments, how changing AI could change data scientist roles, and why passwords are more ubiquitous than ever.
- By Lindsay Stares
- February 9, 2017
Infrastructure speed has reached a plateau. Today's enterprises should be seeking out predictive, automated solutions to improve their enterprise infrastructure.
- By Rod Bagg
- February 9, 2017
When it comes to embedding analytics insights into your business, technology is the easy part. Figuring out what to do and how to do it is much harder.
Making your visualization interactive may involve many different levels of interaction, including providing greater detail, a hands-on feeling, or an invitation to explore.
- By Lindsay Stares
- February 8, 2017
Big data goes beyond volume, variety, and velocity alone. You need to know these 10 characteristics and properties of big data to prepare for both the challenges and advantages of big data initiatives.
- By George Firican
- February 8, 2017
A new class on recognizing fake or distorted data, why data science needs transparency, and the basics of the blockchain distributed database.
- By Lindsay Stares
- February 7, 2017