February 28, 2014
If you've been following our announcements recently, you're well aware that IBM is moving our big data and analytics portfolio inexorably into the cloud.
December 12, 2013
Transactions make the world go round, and high-performance analytics help the planet to rotate even faster on its axis.
August 29, 2013
Just last week we had a very interesting #ibmblu twitterchat on "Controlling Your Data Footprint." Many experts participated in this discussion and many great points were made.
August 2, 2013
Big data need not mean bigger complexity.
July 29, 2013
How is big data changing analytics? How is the role of the DBA changing? Check out the great #ibmblu twitterchat from July 24.
July 10, 2013
Data management has undergone significant change ever since the introduction of online transaction processing systems (OLTP) some 50 years ago. The level of change during this period, however, has not been uniform.
May 17, 2013
In our Friday Data Flick series this week, we look at how companies are achieving an “enhanced 360-degree view of the customer,” which is another of the top five uses for big data (also called “use cases”).
April 4, 2013
Big data has its discontents. The backlash is a necessary reality-check in an otherwise vibrant arena. Often in this industry, when a technology is vogue, the hype can interfere with rational decision making, both among users and among solution providers.
September 17, 2012
Everyone knows everything is bigger in China, and big data is no exception. This is why it is no surprise that big data interest is gaining a lot of momentum in China.
April 3, 2012
When I hear the term inventory management industries that first spring to mind are manufacturing and retail, so I listened closely when I heard a specialist from our financial services team using the term. Banks and other finance companies must exercise tight control of their computing assets to comply with industry regulations. Given the distributed and networked configurations of modern computer systems, meeting regulatory demands can be a challenge and understanding data residing on each machine complicates this already difficult task.