As an IBM Big Data Product Marketing Manager, Christy Maver is responsible for marketing InfoSphere BigInsights for Hadoop. Christy has 14 years of experience with technology marketing and 12 years at IBM. She was a founding member of IBM’s Institute for Business Value, which provides leading-edge thought leadership and practical insights for business executives. She holds a BA in Economics from Princeton University. Follow Christy on Twitter.com/cdmaver
March 5, 2014
In a recent report titled "CIO 100 for 2013," 100 companies were recognized for demonstrating the strategic partnership of IT and business. IBM and several of its clients appeared on its list. This post takes a closer look at the successful big data projects that landed them on this list.
March 4, 2014
My home office window has a direct view to the Hollywood sign. Most days it blends into the background, aside from the occasional gaze during a conference call when I allow my mind to wander to a parallel universe of red carpets, spotlights and my handprints on the walk of fame. Once a year, however, that Hollywood sign comes into full focus: awards season. Yes, awards season is in full swing. Only this year, it’s not just awards season for the Hollywood elite, it’s here for big data as well.
February 5, 2014
In today’s increasingly connected world, machine data analysis is becoming a business imperative. While managing it may be challenging, opportunities abound across multiple industries for those who can tackle this complex data.
January 10, 2014
It’s a new year, and you know what that means.
July 24, 2013
There has been a lot of talk lately about big data and business intelligence.
July 2, 2013
April 4, 2013
One of the recurring themes at yesterday’s “Big Data at the Speed of Business” launch was comsumability, which is just a fancy word for ease of use.
December 6, 2012
Closing the big data talent gap requires tackling the problem from both sides: the people and the technology. Adequately training the data scientists of tomorrow is an obvious and necessary step, but what about the non-data scientists? And what about the technology side? What can we do to make the technology more accessible to the people? If companies are saying that they don’t have the in-house skills to do something with big data, then doesn’t that imply that the existing big data technologies are just too complicated?