January 2015

All posts from January 2015

Managing data at speed requires flexibility and agility

by pm2net on January 30, 2015 , Comments Off on Managing data at speed requires flexibility and agility

In part five of this series we explored Acquire, the first of three key stages within the analytics lifecycle, which provides the ability to acquire and integrate data quickly—foundational to creating an analytics speed advantage. In part six we will look at recommendations and practical actions for the Acquire stage. These recommendations will focus on the flexibility and agility needed to acquire and manage data at the speed necessary to create value.

Source: big data hub

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Data scientists need to nip model overfit in the bud

by pm2net on January 29, 2015 , Comments Off on Data scientists need to nip model overfit in the bud

Overfitting is an unfortunate consequence of top notch data scientists attempting to refine their statistical models. It stems from the tendency to skew data science models by starting with a biased set of project assumptions that drive selection of the wrong variables, the wrong data, the wrong algorithms and the wrong metrics of fitness. Weeding out overfitting whenever and wherever it occurs is the duty of every working data scientist.

Source: big data hub

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Simulating customer cognition with or without neuroscience

by pm2net on January 23, 2015 , Comments Off on Simulating customer cognition with or without neuroscience

Functional simulation, not literal cloning, is the heart of cognitive computing. To understand the cognition of customers or any other human, you should be modeling the higher cognitive, affective and sensory faculties of the mind, not the actual physical components of the brain. Most cognitive-computing professionals see no need to model intelligence down to the neurological level in order to make high-quality predictions of human behavior. Decision science draws on artificial intelligence, cognitive studies and other behavioral sciences. By contrast, the discipline of neuromarketing research is founded on the notion that mixing neurology with psychology is the key to getting inside customers’ heads, by way of their nerve endings. Though neuromarketing may deepen some insights, gauging what’s going on in customers’ minds doesn’t mean you literally need to look into their heads.

Source: big data hub

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Why you may never need to become a data scientist

by pm2net on January 15, 2015 , Comments Off on Why you may never need to become a data scientist

The democratization of data science is the best thing that has ever happened to this discipline. However, many users may never need to upgrade their skills to the level of a professional data scientist. What you truly need is the ability to tap into continuous, proactive and authoritative insights in all aspects of your life. What any of us truly needs is access to cloud services where data-driven analyses generate these insights and deliver them reliably into every application, be it business or personal in nature. And if your job involves being on the front line to the customer—in other words, if you happen to work in a call center, support function, sales office or the like—then you need the full power of customer analytics, big data, cognitive computing and real-time, next best action inside all of your transactional applications.

Source: big data hub

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