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Monday, July 08, 2013

NumberSense Reviewed

I have been looking for books that explain the difference of what I call analytics, in my long time consulting practice and the newly hyped arena of Big Data.   I am always also on the look out for books that I can use with client groups to explain how analytics is powerful.    The explanation has to be positioned with little or no complex mathematics.  The examples have to be clear, and beg for their simple reapplication to new business domains.

NumberSense includes these characteristics.   Easy to understand, non technical examples.  In the social/marketing/economic/sports domains.  Clear positioning about how the problems should be staged.  Not much about how the problems are technically solved, but that is for the data technologists.  Not a how to book, but sets up the crucial cautions very clearly.

I particularly liked the analysis of Groupon data, which clearly defines where claims and analyses can be wrong in marketing.   A good marketing analysis example.

Fung appreciates the fact that while having more, or 'big' data is useful, but it is more important to get the data and its analysis right, especially as it relates to the decision problem being addressed.  Numbersense is paying attention to the origin and context of the data involved, and knowing enough about how the analysis will be applied to the real problem.  Misinterpretation is the worst mistake you can make.

In the final chapter Fung describes a  day in his life as a data scientist.  This was painfully reminiscent of some of my own enterprise experiences.  Its often more difficult getting the data right than solving the technical problem.

As a decision oriented person you don't need to know the technical methods, any more than you need database expertise to create reports.  This books aims at the business problem and solutions, with a strong numerical focus.  Usually with basic math.   The title of the book NumberSense, is that quality of understanding when an analysis is right or going wrong, and what to do about that.   The data in an analysis does not have to be BIG or even complex, just correctly addressed.   The book and more about it:

NumberSense: How to Use Big Data to Your Advantage    by Kaiser Fung .

See also his Numbers Rule Your World blog site for day to day examples.

Examples covered: 

" ... How does the college ranking system really work?
Can an obesity measure solve America's biggest healthcare crisis?
Should you trust current unemployment data issued by the government?
How do you improve your fantasy sports team?
Should you worry about businesses that track your data?

Don't take for granted statements made in the media, by our leaders, or even by your best friend. We're on information overload today, and there's a lot of bad information out there.
Numbersense gives you the insight into how Big Data interpretation works--and how it too often doesn't work. You won't come away with the skills of a professional statistician. But you will have a keen understanding of the data traps even the best statisticians can fall into, and you'll trust the mental alarm that goes off in your head when something just doesn't seem to add up.... "

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