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Data Jujitsu: The Art of Turning Data into Product von [Patil, DJ]
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Data Jujitsu: The Art of Turning Data into Product Kindle Edition

4.7 von 5 Sternen 3 Kundenrezensionen

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Produktbeschreibungen

Kurzbeschreibung

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.

Produktinformation

  • Format: Kindle Edition
  • Dateigröße: 1509 KB
  • Seitenzahl der Print-Ausgabe: 33 Seiten
  • Gleichzeitige Verwendung von Geräten: Keine Einschränkung
  • Verlag: O'Reilly Media; Auflage: 1 (14. November 2012)
  • Verkauf durch: Amazon Media EU S.à r.l.
  • Sprache: Englisch
  • ASIN: B008HMN5BE
  • Text-to-Speech (Vorlesemodus): Aktiviert
  • X-Ray:
  • Word Wise: Nicht aktiviert
  • Verbesserter Schriftsatz: Nicht aktiviert
  • Durchschnittliche Kundenbewertung: 4.7 von 5 Sternen 3 Kundenrezensionen
  • Amazon Bestseller-Rang: #7.052 Kostenfrei in Kindle-Shop (Siehe Top 100 - Kostenfrei in Kindle-Shop)

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Format: Kindle Edition
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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Format: Kindle Edition Verifizierter Kauf
The book describes how to create data products in the area of web 2.0 and gives some really useful examples (Facebook, LinkedIn, etc.) and principles for data or more general software product processes.
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Format: Kindle Edition
Das Buch ist spannend und leicht zu lesen. Mir haben aber Beispiele aus nicht-online Segment gefehlt. Ansonsten ganz gutes Produkt
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Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)

Amazon.com: 3.9 von 5 Sternen 20 Rezensionen
8 von 8 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen A quick but insightful read... 23. Juli 2012
Von Thomas Duff - Veröffentlicht auf Amazon.com
Format: Kindle Edition
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 von 2 Kunden fanden die folgende Rezension hilfreich
2.0 von 5 Sternen A very light introduction 28. Oktober 2013
Von Amazon Customer - Veröffentlicht auf Amazon.com
Format: Kindle Edition Verifizierter Kauf
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 von 2 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen Its a good speed read 6. Januar 2013
Von skyspeak - Veröffentlicht auf Amazon.com
Format: Kindle Edition Verifizierter Kauf
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
1 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Short, good and free 27. Februar 2013
Von Fabio - Veröffentlicht auf Amazon.com
Format: Kindle Edition Verifizierter Kauf
What more could you have?

It's a short text, but very striaght to the point and useful. It's that kind of thing you read and think it's obvious, but never really thought about it in the way it is written.

I recommend this book to anyone working with new products and SPECIALLY if you're thinking of creating a Startup. The book could make good startups better and worse startups die in the frist few minutes.
1 von 1 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Talks about present and past, but where's the future? 25. Januar 2013
Von Charles - Veröffentlicht auf Amazon.com
Format: Kindle Edition Verifizierter Kauf
The book is great for someone that doesn't know anything about the math behind these techniques. Succinct history with examples of successful and unsuccessful Big Data applications. My only complaint is he doesn't really hint toward anything really groundbreaking for the future of the field. Being in the Big Data realm myself, I know there's plenty of titillating stuff casual readers would appreciate.
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