- ISBN13: 9780596157111
- Condition: NEW
- Notes: Brand New from Publisher. No Remainder Mark.
Product Description
In this insightful book, you’ll learn from the best data practitioners in the field just how wide-ranging — and beautiful — working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video.
With Beautiful Data, you will: Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web Learn how… More >>
Beautiful Data: The Stories Behind Elegant Data Solutions
Tags: Beautiful, Behind, challenges, computer, Data, data solutions, Elegant, elegant solutions, insightful book, mars lander, radiohead, Solutions, Stories, vast number
#1 by Donald Park on February 3, 2010 - 5:26 pm
This book is a well assembled collection of academic papers and conference presentations on data mining. I found chapter 4, Cloud Storage Design, to be the most interesting in its description of Facebook’s extensive use of Hadoop. Chapter 8 introduced me to the concept of Web Sockets in HTML5.
Rating: 4 / 5
#2 by JUAN DAZA AREVALO on February 3, 2010 - 7:00 pm
Segeran & Hammerbacher (et. al.) offer an insight on data works where inspiration may find a way. Hopefully any reader may become an author for a further version.
Rating: 5 / 5
#3 by Ira Laefsky on February 3, 2010 - 9:24 pm
From the title, I might have guessed that this was another pretty coffee table book on Information Visualization–Basically, an art book unless you already had the insight and talent to apply its principles to your own work in Data Representation. But, I should have expected (and I did receive) much more from O’Reilly’s efforts in this domain. While the book is indeed beautiful, it more importantly provides a set of carefully described case studies in all phases of the data capture, processing, analysis, communication and visualization life cycle. Detailed descriptions are given of the motivation and design of data capture, analysis and design system in fields as diverse as personal energy consumption (and carbon footprint), mars explorer robotics, high quality market research, interpretation of U.S. Census statistics, and the visualization of DNA databases.
The case study methodology points out the necessity of designing all phases of the data capture, processing, analysis and representation process around the goals, open questions and constraints of the client organization, or user/consumer of the data
whose decisions are being informed. The thinking and design process behind these cases of beautiful data are fully described–this will enable you (or an untalented artist such as myself) to design systems which answer the questions and support the decisions of the individual or organization who needs this data.
–Ira Laefsky
Rating: 5 / 5
#4 by Michael McCown on February 3, 2010 - 9:39 pm
This is a collection of 20 different stories about data – gathering, planning, interpreting, storing, visualizing, etc. I’d like to go through and comment on every story in the book, but then this would be a Cliffs Notes, not a review. Let’s have some highlights:
In “Seeing Your Life in Data”, Nathan Yau tells about developing two projects: “the Personal Environmental Impact Report (PEIR), a tool that allows people to see how they affect then environment… and your.flowingdata (YFD), and in-development project that enables users to collect data about themselves via Twitter”. That in itself is cool; users simply sent formatted tweets (”ate salad”) to track mood, eating, or what have you, and then interact with the data on the site. The difference in the data collection for the two systems is also an interesting discussion, and I liked the insight into the process for choosing the best PEIR visualization.
I think my favorite chapter is titled “What Data Doesn’t Do”, by Coco Krumme. To break away and talk about me for a moment (and isn’t everything, in the end, about me?), I subscribed for some time to a LSAT Logic in Real Life podcast, which explored the fallacies behind our reactions to common or current events. I really enjoyed learning the names and methods of misplaced logic and biases. “What Data…” struck me in a very similar vein. I’ve been trying hard not to quote this chapter, for fear that I’ll just type it out. Still, I can’t resist my absolute favorite paragraph. It begins with the header “Data Alone Doesn’t Explain”
“People explain. Correlation and causality, you may have heard, make strange bedfellows. Given two variables correlated in a statistically significant way, causality can work forward, backward, in both directions, or not at all. Statisticians have made a hobby … of chronicling the abused of correlation, like old ladies clucking at the downfall of traditional values in the modern world.”
Beautiful. Again, I’d love to give a review of each chapter, but then you’d fall in love with my writing instead of Beautiful Data. Yeah, of course you would.
Finally, and most shallowly, it’s a really pretty book. Check out the cover art! And that’s without considering the 70 color plates, including everything from user surveys and line charts, to laser data and DNA. One, two…that’s 33 words to effectively say, “Pretty pictures!”
Let’s be serious for a moment, though. This book was, to me, truly extraordinary and truly entertaining. I read it in pieces over the course of a few weeks, and it was lovely to take in one story – one angle on data problems or applications – and muse on it on and off until I had a few minutes to read the next. It’s a book that lends itself to piecemeal reading, jumping around, and rereading at will. And it’s one I recommend not just to IT pros, but to everyone.
Rating: 5 / 5
#5 by Thomas W. Gonzalez on February 3, 2010 - 10:47 pm
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.
Rating: 3 / 5