Data Jujitsu: The Art of Turning Data into Product

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"O'Reilly Media, Inc.", Nov 14, 2012 - Computers - 26 pages
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Acclaimed data scientist DJ Patil details a new approach to solving problems in Data Jujitsu.

Learn how to use a problem's "weight" against itself to:

  • Break down seemingly complex data problems into simplified parts
  • Use alternative data analysis techniques to examine them
  • Use human input, such as Mechanical Turk, and design tricks that enlist the help of your users to take short cuts around tough problems
Learn more about the problems before starting on the solutions—and use the findings to solve them, or determine whether the problems are worth solving at all.
 

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I found this to be a very interesting and insightful article on data science as it is practiced in the real world. However, your impressions of this short e-book will strongly depend on your expectations. If you are looking for an detailed and technical how-to book, then you will be severely disappointed. I think that people who will most appreciate this e-book article are either those who have very little to no experience with data science, or potentially the high-level experts and veterans of the field. For the first group this e-book could serve as a gentle introduction to the field in the most general way, while the latter could appreciate the big picture take by one of their very experienced colleagues. I am definitely in the first group, and I really enjoyed this short e-book.
The central idea of this e-book is that in design of data-driven products it helps to use the actual usage of the product as a guide and a driving force. This is where the Jujitsu metaphor comes in play: just like a practitioner of that martial arts relies on the opponent's own attacks and forces and tries to martial them to his own advantage, so also a designer of a data-driven product will ideally try to use the "gravitational pull" of data and its use to his advantage.
Patil illustrates his ideas and concepts with several useful examples, mostly from his work at LinkedIn. These are useful examples in their own right, as they also give the reader a few insights into how LinkedIn actually connects people. Some of the ideas in the book are already well known to most software designers and entrepreneurs (good data structures are crucial, try to design a minimally functioning prototype and then iterate, etc.), but others are a bit counterintuitive and novel.
This short e-book is very readable and well written, something that one can never take for granted for a geeky book on data science. It's an interesting read and I was able to finish it in a single sitting.
 

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About the author (2012)

DJ Patil has held a variety of roles in Academia, Industry, and Government. These include, VP of Product at RelateIQ which was acquired by Salesforce. The Data Scientist in Residence at Greylock Partners. The Chief Scientist, Chief Security Officer and Head of Analytics and Data Product Teams at the LinkedIn Corporation. Additionally he has held a number of roles at Skype, PayPal, and eBay. He is known for co-coining the term Data Scientist.

As a member of the faculty at the University of Maryland, his research focused on nonlinear dynamics and chaos theory and he helped start a major research initiative on numerical weather prediction. As an AAAS Science & Technology Policy Fellow for the Department of Defense, Dr. Patil directed new efforts to leverage social network analysis and the melding of computational and social sciences to anticipate emerging threats to the US. He has also co-chaired a major review of US efforts to prevent bioweapons proliferation in Central Asia and co-founded the Iraqi Virtual Science Library (IVSL). In 2104 he was selected by the World Economic Forum as a Young Global Leader.

More details can be found on his LinkedIn profile: http://www.linkedin.com/in/dpatil and can be followed on twitter @dpatil.

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