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Beautiful Data (Anglais) Broché – 31 juillet 2009

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3,7 étoiles sur 5 21 commentaires client

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Descriptions du produit

Beautiful Data Helps you explore the opportunities and challenges involved in working with the many number of datasets made available by the Web. This book also helps you learn how to visualize trends in urban crime, using maps and data mashups, and discover the challenges of designing a data processing system that works within the constraints of space travel. Full description

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Amazon.com: 3.7 étoiles sur 5 21 commentaires
57 internautes sur 57 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Occasionally brilliant discussions on data and what data can and cannot do 12 octobre 2009
Par Amazon Customer - Publié sur Amazon.com
Format: Broché Achat vérifié
"Beautiful Data" is a collection of essays on data; how people have transformed it, worked within its confines, and offers a glimpse of where we might go. Many of the essays are wonderful snippets into how some people perceive data while others fall flat. Overall its a mostly enjoyable read that helps open up your mind to new potentials.

First a disclaimer; I am not a data person. However I've been involved, fairly heavily, in the data field. In the parlance of the world, I'm a back end person. However I'm always trying to think about the front end; how will things be used and what information can we gleen from the system (or systems). With that in mind, this is a book that speaks to me - its all about the front end.

Some of the best essays in the book would be:

The first essay by Nathan Yau he talks very much about user created data and personal databases (knowledge bases). What's exciting here is how he takes data already out there, data you have provided, and creates something useful and yes, beautiful, out of it.

The Second essay by Follett and Holm really gets down to how if you want the data, you need to present it in a way that brings people into the process. As someone who has a slight crush on the statistics and practices in polling (and designing poll questions) this essay really was a fascinating read.

The third essay by Hughes detailed how he handled images on the Mars mission. There wasn't anything here that wasn't done in embedded systems 15 years ago; still it was a great walk down memory lane since I used to program embedded imaging systems.

Chapter 4 really hit home PNUTShell is cloud storage and data processing in real time. This really is the stuff of the future.

Chapter 5 by Jeff Hammerbacher really didn't offer too many insights but his writing style is fluid and fun plus he offered a glimpse into how Facebook grew.

We then have the slow section of the book - Chapter 8 on distributed social data had promise but it read more like a company white page than an interesting article. Same with Chapter 12 [...].

Thankfully chapter 10 on Radiohead's "House of Cards" video was there - and here we are presented with true beauty in data - beautiful enough to create a music video out of!

I'm still on the fence with Chapter 13 - What Data Doesn't Do. It was an interesting chapter but it felt both too long and too short at the same time. I almost felt that in the author, Coco Krumme, were to write a book on this topic, I'd want to read it. However her essay was not the right vehicle.

Finally, the last chapter - "Connecting Data" was a truly inspiring piece; one that offers up paths for the future. I am sure a few start ups will form over the questions posed in by Segaran (or maybe the questions to the questions).

Overall there were enough strengths to overcome the weak chapters. My main complaints are trivial; poor binding of the book, too many PhD candidate papers and not enough from out in the trenches. I'd love to see something from Stonebreaker here; its hard to talk about beautiful data and not have him in it. Or forget [...]and talk about many eyes. Or map reduce. Still, "Beautiful Data" succeeds. It opened up my mind to different possibilities for data representation and usage.
2 internautes sur 2 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Nice example on how to get the best out of data analysis 17 décembre 2011
Par Oscar Cassetti - Publié sur Amazon.com
Format: Broché Achat vérifié
This book is very entertaining if you are interested in data analysis, mining and visualization. It is not too technical. It is more a top view of some case studies in data analysis / mining.
Since this is a collection of "stories" some of them are very interesting e.g. about Census data, other were in my opinion somehow less relevant.
It is definitely inspirational and it is a good guide to see what other people were able to achieve through data mining. You might find that somebody already solved a problem similar to yours.
1 internautes sur 1 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 great compendium 26 avril 2013
Par dchow - Publié sur Amazon.com
Format: Broché Achat vérifié
insightful, case-study descriptions from leading voices in area. gives real sense of how and what data science is about. foundation book. incredible used book price - even sweeter.
3.0 étoiles sur 5 Three Stars 4 septembre 2014
Par Ben Rollert - Publié sur Amazon.com
Format: Format Kindle Achat vérifié
A couple amazing chapters that make the book worth it, but the rest is quite bland.
20 internautes sur 25 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 Good content, lousy print quality 1 septembre 2009
Par Thomas W. Gonzalez - Publié sur Amazon.com
Format: Broché Achat vérifié
While the content of this book is interesting and informative, I am struck with what lousy print quality it is. For a $40+ book you would expect a hardback, or at least a paperback with thick stock pages and color plates that actually look good. It was hard for me to appreciate the content when it felt like each page (or the cover) was going to rip because they were such thin and poor quality stock. The color plates are washed out and pixelated. I was expecting the same high quality we got with "Beautiful Code". O'Reilly usually does a much better job. That said, if these types of aesthetics don't bother you (although with a title like "Beautiful Data" I would question that it wouldn't) the book itself is an interesting read.
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