Jumat, 15 Februari 2013

[E568.Ebook] Ebook Data Jujitsu: The Art of Turning Data into Product, by DJ Patil

Ebook Data Jujitsu: The Art of Turning Data into Product, by DJ Patil

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Data Jujitsu: The Art of Turning Data into Product, by DJ Patil

Data Jujitsu: The Art of Turning Data into Product, by DJ Patil



Data Jujitsu: The Art of Turning Data into Product, by DJ Patil

Ebook Data Jujitsu: The Art of Turning Data into Product, by DJ Patil

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Data Jujitsu: The Art of Turning Data into Product, by DJ Patil

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.

  • Published on: 2012-11-14
  • Released on: 2012-07-19
  • Format: Kindle eBook

Most helpful customer reviews

8 of 8 people found the following review helpful.
A quick but insightful read...
By Thomas Duff
O'Reilly recently released one of their free Radar Reports titled Data Jujitsu: The Art of Turning Data into Product by DJ Patil. This short (24 pages) report is packed with interesting insights and actionable information that will change the way you look at your next project. It's very much worth the minimal investment in time to download and read.

Contents:
Data Jujitsu; Use Product Design; When In Doubt, Use Humans; Be Opportunistic For Wins; Ground Your Product In The Real World; Give Data Back To The User To Create Additional Value; No Data Vomit; Expect Unforeseen Side Effects; Improving Precision And Recall; Subjectivity; Enlisting Other Users; Ask And You Shall Receive; Anticipate Failure; Putting Data Jujitsu Into Practice; About The Author

The author thoroughly knows his topic, as he is a data scientist with real-world experience working on well-known sites such as LinkedIn. That is an example of a site that is driven heavily by data and connections between data. Observing what the site is actually used for, as well as what people attempt to accomplish, is what adds the additional value over time.

Given that this is a report rather than a "book", I found that the ideas and actionable content could be found on nearly every page. I thought his approach to solving the data issue prior to solving the application problem both refreshing and insightful. Why spend a fortune (both time and money) to create a product only to find out that no one has the problem you want to solve? Or worse, you spend far too much time solving the wrong problem (usually the more complex and "interesting" one) rather than the one that people would spend money to have solved. A cheap and usually non-scalable approach to collecting the data is preferable, as it allows you to figure out what needs to be the focus and what can be ignored. An example of that approach is Amazon's Mechanical Turk. MT can be a quick way to use humans to solve a problem (such as visual recognition) instead of spending untold amounts of time building a computer-based visual recognition system that may be tangential to the actual problem you're trying to solve.

Another interesting point was to have a conversation with the user instead of just having them fill in data. If you can design the interface to help the user enter "clean" and relevant data, while at the same time giving them feedback and value, they become your partner in finding answers and relevant links between data points.

Finally, I can't let my favorite title for a chapter/section go unmentioned... Data Vomit. It's what happens when you decide to focus on the amount of data coming back instead of focusing on what people are doing with it. Focus on actions, not volume of data returned. This hits home as it's very common to have users ask if we can generate data in formats x, y, and z. When you ask *why* they want that feature, the answer is often "I just thought it might be nice to have." Instead, I need to focus on what they actually want to accomplish, not on how many different contortions we can twist the data into...

Go ahead and download the report from either Amazon or O'Reilly. It'll take less than an hour to read, and you'll get far more than that in return.

Disclosure:
Obtained From: Publisher
Payment: Free

2 of 2 people found the following review helpful.
A very light introduction
By Amazon Customer
While the book was free, I didn't feel you could get any more infomation than you would from a quick web search. While this was probably the intention of the book, the martial art metaphore doesn't quite fit as martial art is something fine and precise, not broad and general. A more fitting title would be - first time causal cart racing.

2 of 2 people found the following review helpful.
Its a good speed read
By skyspeak
This is a great speed read. I would highly recommend this to practitioners or people evaluating Big Data technology. Pretty good for a speed read

See all 23 customer reviews...

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