Optimize Operations and Reduce Fraud

Why advanced analytics projects are different from traditional IT

December 9, 2014
To fulfill the promise of analytics, we must put a lot more effort into delivering these projects right, the first time. We must think through each of the traditional success criteria and ask ourselves the burning question: how is delivering analytics different? This starts from gaining executive support, creating a business case, putting a team together, conducting proof of concept, quantifying benefits realization and socializing results for enabling analytics driven organizational change. Read More

Realizing a return on big data investments—within a year

December 2, 2014
In 2014, there were several important shifts that occurred in the world of big data that business executives around the globe cannot afford to ignore. In part one we introduced four transformative shifts affecting the fast-paced digital marketplace; now in part two we will take a closer look at the first two shifts. Read More

Bust myths to gain insights and make data work for you

November 10, 2014
Data is the new natural resource, and those who can harness it will be leaders. But, there are many myths about how to make data work for an organization. During the Information Management Keynote at Insight 2014, IBM busts these myths. In her post, Harriet Fryman, vice president of Information Management at IBM, shares highlights and her perspective on how to make data work for you and your company. Read More

The CDO is in the driver's seat of the new data-driven business

November 5, 2014
Big data has matured, moving beyond the peak of its initial hype and is moving ahead into its promised plateau of productivity. Read More

Three information infrastructure myths debunked

November 4, 2014
The Information Management keynote session at IBM Insight 2014 brought new product offerings, memorable stories and answers to some common information infrastructure myths. Read More

Barriers to entry for early adopters of IBM Watson

November 3, 2014
There have always existed significant barriers to entry for early adopters of any new technology. For example, all the miles of cable that needed to be run in order for the world to take advantage of the miracle of electricity. Now consider the computer: devices that were capable of processing only the most rudimentary of algorithms used to fill rooms, and were programmed using cryptic punch cards. Now the world has been introduced to IBM Watson, the first and only (as of the time of this writing) commercially available artificial cognitive intelligence. Read More

Flexibility is key to a smooth big data and analytics journey

October 26, 2014
Embarking on a big data and analytics journey is like setting off on a worldwide tour. You have an idea of what you want to do and see, and what you’ll need, but you must be flexible—your adventure will undoubtedly take some unforeseeable turns! IBM’s new Big Data & Analytics Solution Accelerator offering provides you with access to a catalog of all the big data and analytics software that may be required throughout your journey, with the flexibility to leverage what you need, when you need it.   Read More

How to protect against sensitive data leakage

October 23, 2014
The average organization loses $3.2 million to data breaches, up 15% from 2013. It's time to blend log analysis, real-time and predicative analytics to enable a new big data security analytics strategy.  Read More

The clairvoyance of the Internet of Things

October 17, 2014
Would you want to know about a potential problem before it becomes a real problem? Especially if it saves time and money? I can embrace having that kind of knowledge, but just how does that happen? Read More

Discrimination drives the need for ethics in big data

October 13, 2014
Big data and analytics are profoundly affecting the world around us. One of the focal points of my postings has been how big data and analytics affects, specifically, our personal privacy. An old and perhaps far too familiar twist on this has risen to the forefront of discussion and that is the issue of whether big data and analytics will be used to discriminate against the less fortunate (or perhaps even “the one percent”). Read More

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