This podcast features Doug Thompson, executive architect, Information Governance and master data management (MDM), at IBM, who discusses the various factors that make data integration challenging and how one can overcome them. Thompson also shares his views on hybrid- and cloud-based data
Data scientists and others often encapsulate big data by its dimensions known as the four Vs: volume, variety, velocity and veracity. But when considering big data as a source for insight to enhance decision making, it may be best characterized by its three Cs—confidence, context and choice—with
A majority of organizations today claim they have a competitive advantage because they are using big data and analytics. But, if everyone is claiming that, who really has the competitive advantage? The ones that do more predictive analytics? The ones that can do it cheaper? My bet is that it’s the
If most organizations are using analytics to improve customer interactions, optimize supply chains and reduce financial risk then where does the advantage in today's marketplace come from? The IBV 2014 Analytics study will explore how organizations are creating a competitive advantage in today's
In the big data scheme of things, you can talk about the "3 Vs," the "4 Vs," or as many "Vs" as your fevered imagination can spin out. The "3 Vs" point to the "big" dimension of the big data phenomenon, but when you shift the focus from "big" data to "all" data, the fourth V becomes a cleaner fit.
In my first post I introduced the idea that most “big data” isn’t really big at all, and doesn’t conform to Gartner’s 3V’s. Instead, I've suggested that there’s benefit in focussing on “broad data”, or the use of many different sources of data to give us richer information. We put forward 4O’s of
“Big data” is an area of intense interest in the IT change field right now. CIO’s are being told that this is something they need to address, and lots of big data solutions are being bought and sold. Cynics may feel that there is a lot of hype around big data, but many people clearly believe
IBM data scientists break big data into four dimensions: volume, variety, velocity and veracity. This infographic explains and gives examples of each.
For updated figures, please refer to the infographic Extracting business value from the 4 V's of big data.
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Matt Aslett, research director at 451 Research, wrote the foreword for the new book Harness the Power of Big Data, and he shares here some of his thoughts on the topic - and the book.
‘Big Data’ is a curious phrase. Since I first encountered it some three and a half years ago, it has come to be one
If there’s more and more data arriving and time isn’t expandingi, then data must be arriving at greater and greater velocity.
In my last post I talked about Variety in the Volume, Variety, Velocity triumvirate. There’s more to be said about that, but first I’d like to take a run at Velocity. We’ve