You might not think of data as a living thing, but it does have a life cycle. For some data, it's fleeting, but other data may live for decades. How do you determine how long to keep data and how to handle it while it's in your care?
In this #BigDataMgmt Twitter chat, we will discuss methods for
In a recent article published on Information Age, Richard Lee said there is much discussion these days about data privacy and security, but precious little about trust. He expressed concern: "Trust is hard to achieve, easy to lose and almost impossible to regain." Richard joined us to discuss how
I recently attended the Gartner Master Data Management conference in Europe. Andrew White, a senior Gartner analyst, shared a statistic during the opening keynote presentation that stuck with me—the statistic is this:
"Roughly 1 in 3 organizations will suffer an information crisis in the next 2
In the marketing segmentation scenario we discussed in my last blog post, cost savings from improved mailings did not provide enough savings to make an MDM project profitable. This is not unusual in that, in addition to cost savings, new revenue opportunities are required to justify the investment
There are many paths to actively engaging consumers in their health and wellness, and the ONC Patient Matching Final report provided yet another avenue. In my blog I mentioned consumer engagement as a path to better data quality, but the value is really very broad. Therefore, it is important that
Big data projects often involve exploring new business challenges and using new technology alongside existing applications. But who is doing this work? What skills and personalities are needed? Where should management of the big data "team" live, and is the team all in the same department or cross-
In my last post, I discussed a relatively simple business case scenario where an enterprise intends to implement MDM because their current process heavily relies on a third party supplier of customer data.
Typically, though, things aren’t quite that simple.
Today, let’s discuss a more complex MDM
The biggest roadblock to big data and analytics capitalization stems from people, not data. A fragmented approach to investments and decisions can result in a breakdown of trust between different groups of people who may be accessing, interpreting and using data in different ways. The right level
IBM’s Technical Consultancy Group led this academic colloquium last week on big data and analytics to collaborate with UK academics on research, teaching and technology. This was a high impact gathering of top-tier academic and industrial expertise discussing social, media and human-computer
IBM’s Technical Consultancy Group led this academic colloquium last week on big data and analytics to collaborate with UK academics on research, teaching and technology. The colloguium was a high impact gathering of top-tier academic and industrial expertise identifies big data architecture and
Bob Griffin, VP of IBM Industry Solutions discusses the deep impact fraudulent activities have on organizations and consumer confidence. He introduces a new counter fraud solution from IBM designed to help prevent and intercept attempted fraud, and employs advanced intelligence allowing
This is part 14 of our series on the findings and text from the IBM Institute for Business Value’s latest study and paper “Analytics: A blueprint for value - Converting big data and analytics insights into results” from my colleagues Fred Balboni, Glenn Finch, Cathy Rodenbeck Reese and Rebecca
Big data and analytics technology can reap huge benefits to both individuals and organizations—bringing personalized service, detection of fraud and abuse, efficient use of resources and prevention of failure or accident. So why are there questions being raised about the ethics of analytics, and