Data lakes have been widely misunderstood, but they are now benefiting from new best practices -- helping organizations gain significant value.
- By Dale Kim
- February 16, 2017
With the increasing demand for data science professionals, what skills are necessary to succeed in our new digital world?
- By Devavrat Shah
- February 14, 2017
Data science today is extremely labor-intensive. The automated or quasi-automated features widely used in self-service BI aren't commonplace in data science, but Gartner says that's about to change.
Three things that distinguish data prep from the traditional extract, transform, and load process.
- By Wei Zheng
- February 10, 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
Four steps you can take to retain top talent by ensuring your analysts stay productive and engaged in their work.
- By Pete Reilly
- February 6, 2017
To get full business value from big data and other new data sources, many organizations use a data lake atop Hadoop to capture, process, and manage diverse data at scale for business analytics.
- By Philip Russom
- February 2, 2017
As enterprises look to put their best foot forward in 2017, many are increasingly turning to text analysis to improve customer experiences and business processes.
- By Terry Lawlor
- February 1, 2017