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.... "

Herman Miller's Living Office

We worked with Herman Miller in the area of innovative office design.  This is a short article on their concept of the living office.   Although I have not been close to this space for a while,  methods like P&G's Business Sphere are related.  More about the Living Office concept.

Data Mining Concepts and Techniques

Bought some time ago, but finally exercised in some detail:  Data Mining: Concepts and Techniques, by Jiawei Han and Micheline Kamber.   There are later editions than mine, but this is a very good, though mostly technical introduction.  Recommended at least as a reference for techniques.   We used a number of these in the enterprise

Private Label Brands Hold Ground

An indication that private label brands are holding their own after a slow recovery.   " ... While private labels have existed for some time, the recession proved to be the inflection point for them to become a true force in the marketplace. And now that the economy is improving, private labels continue to increase in popularity due to both their improved quality and relatively lower price compared to national brands..... "  Good detail in this article.

Query-less search

An examination of query-less, or parameter-less search in Google Operating System.  And the mention of a Google patent in the space.  And its ultimate integration in Google Now.  We explored the idea with MIT researchers.  A researcher writing a document would have parallel searches invoked by a combination of the domain the researcher was working in, and the previous writings of that researcher and their colleagues.   Links between these searches would be captured and presented as needed.

Visualization Books: Incomplete

The Economist looks at a number of information and data visualization books.  What they look at is good, but is very incomplete.  Largely based on infographics, and does not include the ability to interact with changing data.   When I see something that is called an 'infographic' or is clearly that, it screams to me that it is both incomplete and static.  Thus fundamentally wrong.   Lots new is out there today.  Worth a scan.

Crowds vs Innovation

In Innovation Excellence:  It should be remembered that innovation is often be an act of going against the crowd.   Creative people do go against the crowd: " ... At minimum, they do their own thing. At best, they lead the crowd. Highly creative people tend to be non-conformists who do their own things irrespective of the crowd. Some purposely go against popular trends in order to demonstrate their uniqueness and creativity. Others, often those who are most creative, often seem blithely unaware of the crowd, so focused are they on doing their own things.  ... "