Comments about O'Reilly Media Beautiful Data:

Beautiful Data collects together a diverse set of essays on data collection, visualization, processing, and analysis. What interested me most was the wide variety of application areas in which data is the "secret sauce". The essays range from broadly philosophical to deep in the technical details: so you're likely to find something at your level of interest, though that also means that a significant part of the book won't hit your level.

Jeff Hammerbacher's chapter on Information Platforms and the Rise of the Data Scientist is a good example. It discusses Facebook's history of scaling its data storage and analysis capabilities, starting with custom scripting based on SQL, moving to data warehousing and then beyond to Hadoop and related tools. "More data, simple models" is the processing style that characterizes many such Big Data enterprises today.

Other valuable chapters for me:
* Data Finds Data (Jeff Jonas and Lisa Sokol)
* Natural Language Corpus Data (Peter Norvig)
* Connecting Data (Toby Segaran)

While you're not likely to find a solution here to specific technical problems, there's a good chance you'll find something either to broaden your horizons or give you some new ideas.

(Disclosure: I received a free copy of this book through O'Reilly's blogger program.)

Comments about O'Reilly Media Beautiful Data:

Based mainly on its title and cover image, I anticipated Beautiful Data would be something more like Jonathan Harris meets a college math book. However, the book is neither filled with visual representations of information, nor is it heavy on the equations. Rather, it's a collection of individual essays all loosely tied to the topic of data usage.

Don't look for how-tos, lectures, or any mechanics. This book is the liberal arts version of computer science. Thirty-nine individuals, each with varying degrees of experience and all covering an array of industries, present stories on how they use data and how data have influenced their work. Their case studies and examples sometimes touch on the philosophy of data and analysis and occassionaly are intimate portrayals of the marvels and shortcomings experienced when dealing with information.

Offering alluring glimpses into the projects and data centers of organizations like Facebook and Google, graduate student research, and the making of a Radiohead music video, these are stories of data experiences. Beautiful Data feels a bit like bedtime reading for the data scientist, statistician, or programmer. When you're done going through the stacks, logs, and code of the day, choose a story and learn how other people are capturing, moving, and understanding bits of information.