Category: Analytics

Top 5 Reasons Why Big Data and Analytics Projects Fail – Part 1

A lot has been written about success and failure of Big Data and Analytics projects in recent times. Unfortunately, most of the articles and blog posts on this subject fail to highlight real reasons why Big Data projects fail. Given below are top 5 reasons, in my opinion, why most Big Data and Analytics project

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Category: Analytics

How to Profit from Big Divide of Big Data

When it comes to Big Data and Analytics solution implementations for enterprise clients/large business organizations, I see a big divide between what functionality business users want and are demanding from their CTO or IT organization and the functionality that CTO or IT organization can deliver. I would like to call this gap as “Big Divide

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Category: Analytics

Google Flu Trends: Importance of Veracity, the 4th “V” in Big Data

A lot has been written recently criticizing Goolge’s Flu Trends – a flu tracker service that predicts flu activity based on specific search terms using aggregated Google search data and estimates current flu activity around the world in near real-time. For more, read How does this work? Science magazine has recently published an article titled

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Category: Analytics

Big Data and Analytics: What to expect in 2014

Last year was a great one for technology professionals, consultants and practitioners working in the area of Big Data and Analytics. And 2014 promises to be even better. Given below are three main reasons why 2014 will be a spectacular year for those of us in Big Data and Analytics: 1) Investments in very large

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Category: Analytics

From Data to Information to Insights: Changing Role of #CIO

There was a time not too long ago (late 1970s to be precise) when companies use to have Electronic Data Processing department and EDP Managers to manage data processing function. EDP department evolved to become Management Information Systems department in early 1980s and MIS Manager ran the show when it came to ‘computerization’ initiatives as

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Category: Analytics

Predictive Analytics: A Force Multiplier for Big Data

Force Multiplier, a noun, means something that increases effect of the force. In military usage, force multiplication refers to “an attribute or a combination of attributes which make a given force more effective than that same force would be without it” (for more, see this). Big Data, which is characterized by three Vs, namely Volume, Variety

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Category: Analytics

Big Data and Rise of Predictive Analytics

Back in mid 1990s, when I was a Ph.D. student,  one of the professors asked me what my career goal was and I said: “To help clients serve their customers better through use of Information Technology and Analytics“. After completing my Ph.D. in November of 1998, when the IT revolution in Enterprise Solutions was about to take

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Category: Analytics

5 Ways Big Data Are Fundamentally Changing Information Systems

A lot has been said and written lately about whether Big Data revolution is for real or it is one more hype that will die down soon as tech world moves on to the next fad. In my opinion, Big Data  is a game changing revolution that will fundamentally change how information is collected, stored, managed

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Category: Analytics

Big Data Ecosystem

Here’s a very good chart of big data eco-system prepared by Matt Turck and Shivon Zilis (see this link for more). Like the way they have classified major big data players across Infrastructure, Analytics, Applications and Data Sources. My take on this ecosystem is that we are going to see a lot of action on

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Category: Analytics

Data Rich, but Information Poor: Problem or Opportunity?

It is not uncommon to hear the phrase “Data Rich, but Information Poor” in the context of enterprise information systems. This is especially true when it comes to Big Data, given the three Vs of Big Data, namely Volume, Variety and Velocity (read this for more). What seems like a big problem posed by data deluge is in

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