In celebration of the O'Reilly Strata Conference, we have seven new and essential data products available for review. Contact me with the books and/or video you're interested in reviewing.
—Mary Rotman, maryr@oreilly.com
New Data Titles from O'Reilly
 Pages: 66 |
21 Recipes for Mining Twitter Distilling Rich Information from Messy Data by Matthew A. Russell  Millions of public Twitter streams harbor a wealth of data, and once you mine them, you can gain some valuable insights. This short and concise book offers a collection of recipes to help you extract nuggets of Twitter information using easy-to-learn Python tools. Each recipe offers a discussion of how and why the solution works, so you can quickly adapt it to fit your particular needs. |
 Pages: 58 |
25 Recipes for Getting Started with R Excerpts from the R Cookbook by Paul Teetor This short, concise book provides beginners with a selection of how-to recipes to solve simple problems with R. Each solution gives you just what you need to know to get started with R for basic statistics, graphics, and regression. These solutions were selected from O'Reilly's R Cookbook, which contains more than 200 recipes for R that you'll find useful once you move beyond the basics. |
 Pages: 42 |
Data Source Handbook A Guide to Public Data by Pete Warden If you're a developer looking to supplement your own data tools and services, this concise ebook covers the most useful sources of public data available today. You'll find useful information on APIs that offer broad coverage, tie their data to the outside world, and are either accessible online or feature downloadable bulk data. You'll also find code and helpful links. |
 Pages: 40 |
Data Mashups with R A Case Study in Real-World Data Analysis by Jeremy Leipzig, Xiao-Yi Li Data analysis is more than means and standard deviations. This ebook is a case study of how you can push R into new territory to analyze online real-world data. The authors scrape public foreclosure records for Philadelphia, geocode them, plot them by county, and analyze the results, using R facilities to interact with web servers, parse HTML and XML, and more. |
 Pages: 50 |
Scaling MongoDB Sharding, Cluster Setup, and Administration by Kristina Chodorow Create a MongoDB cluster that will to grow to meet the needs of your application. With this short and concise ebook, you'll get guidelines for setting up and using clusters to store a large volume of data, and learn how to access the data efficiently. In the process, you'll understand how to make your application work with a distributed database system. |
 Pages: 76 |
Writing and Querying MapReduce Views in CouchDB Tools for Data Analysts by Bradley Holt A practical guide to web developers who need to scale their CouchDB database instances. The basic concepts behind CouchDB's scalability (i.e. its distributed shared nothing architecture) will be covered as well as:
|
 Run Time: 3 hours 12 minutes |
Matthew Russell on Mining the Social Web by Matthew A. Russell Learn techniques for mining the vast wealth of Twitter data in this entertaining video course. By looking in-depth into a friendship network and analyzing the Twitter stream of top-tweeter Tim O'Reilly, author and data analyst Matthew Russell shows you how easy it is to uncover valuable Twitter data with basic Python tools and pragmatic storage technologies such as Redis and CouchDB. |
For a review copy or more information please email maryr@oreilly.com. Please include your delivery address and contact information, as well as details on where you'll post your review.
About O’Reilly
O’Reilly Media spreads the knowledge of innovators through its books, online services, magazines, and conferences. Since 1978, O’Reilly Media has been a chronicler and catalyst of cutting-edge development, homing in on the technology trends that really matter and spurring their adoption by amplifying “faint signals” from the alpha geeks who are creating the future. An active participant in the technology community, the company has a long history of advocacy, meme-making, and evangelism.