When thinking of use cases for big data analytics, consider your need for immediacy. Do you have the need to know now, not just the ability to know now? In other words, would you do something differently at that moment if you knew the answer immediately?
What if you could learn what’s happening as it’s happening, and use what you learn to change what happens next? Sounds like a futuristic sci-fi movie itself, doesn’t it? But it’s not only possible now, it’s happening - even in an industry that hasn't changed much in 50 years.
There is no doubt about it: the practice and profession of marketing is changing… rapidly.
This evolution-level transformation is being seen in virtually every industry across B2C and B2B organizations. It’s being heard by both in-house marketers and outsourced marketing service providers and
This is the first in a series of blogs that will explore the role of big data in government.
Government’s huge variety of responsibilities including defense, national security, social programs, taxation, environmental stewardship and much more, both require and generate massive amounts of data. The
It’s difficult to read a banking technology article or go to a conference without hearing about big data. Most of us now believe that big data is more than just hype, that it can offer business benefits to those that can leverage big data into new business capabilities. But a common question I hear
In Part I of this series, we looked at the key considerations for an analytic enterprise to stay competitive in today’s world, and in Part II we discussed how those translated into imperatives for a supporting big data platform. In Part III we covered how IBM applied those considerations and
For 27 years, at a site bordered to its south by the bank of the Moskva River, a deep hole and sparse foundations spoke of a country whose resources proved insufficient fuel for its leader’s vanity. In 1812, when an early and hard winter forced Napoleon Bonaparte’s army out of Russia, Emperor
Predictive analytics encompasses a variety of statistical techniques from modeling, machine learning, data mining and others that analyze current and historical facts to make predictions about future events. In business, predictive models exploit patterns found in historical and transactional data