February 20, 2014
HIMSS14 attendees are in for a treat this year; in addition to the amazing educational sessions and exhibits, visitors will have the opportunity to an exciting story about real-time analytics for research and data quality.
October 28, 2013
Big data means more data – from more sources, in more formats. It also involves data that is created at a more rapid pace. All of those factors make it harder to establish context. Where did this data come from? How much do you trust it? What steps were taken to correct, or massage, the data?
October 7, 2013
Protecting and security sensitive big data is necessary to ensure data is shared for new forms of analysis.
Living the Big Data Dream: Confidence, Confidentiality and Continuous Automation in the 21st Century
September 26, 2013
Big data is about much more than scaling, accelerating and broadening your analytic applications.
September 25, 2013
At a recent IBM event focused on building confidence in big data, a highlight was a wide-ranging discussion by a panel with very diverse background
September 24, 2013
Confidence in big data is highly variable. Some data sources have inherent uncertainty. So why shouldn’t you spend as much time as needed to make big data perfect? Time. You simply don’t have enough time to sort out every data irregularity, every ambiguity, every incomplete attribute.
September 20, 2013
Confidence (aka Veracity) in Big Data is one of the central themes that has emerged recently in the Information Governance community.
September 19, 2013
Openness is where the world is headed. It’s the core principle in truly agile governance of a dynamic, complex, smarter planet. Openness means many things to many people. From a big-data perspective, we can break down the key dimensions of openness as follows:
September 17, 2013
Confidence in big data is essential. Without confidence, decision-makers may not act on big data insights – which would completely negate the benefits of big data in the first place.
September 9, 2013
Most organizations today still treat data as a raw material to be mined, with industrial processes for staged production. Organizations invest millions in capturing, refining and governing the use of information as an attribute of business activity.