Getting log data is not an IT challenge.  But the information security challenge and a huge struggle for those who are tasked with it, is making sense of a near infinite amount of data. 

In Information Security Analytics: Finding Security Insights, Patterns, and Anomalies in Big Data, authors Mark Talabis, Robert McPherson, I. Miyamoto and Jason Martin have created a brief guide that shows how you can take the myriad raw data, and turn it into meaningful analytics.

The authors focus on the methods that are particularly useful for discovering security breaches and attacks, which can be implemented via either free software, or using commonly available software.

Like most titles on data analytics, the book places a heavy influence on R, is a programming language and software environment for statistical computing.

The book is a good how-to guide with plenty of coding examples, to show the reader how to effectively use the tools to make sense of the data they have.

For those new to the topic of data analytics, Data-Driven Security: Analysis, Visualization and Dashboards by Jay Jacobs and Bob Rudis is the gold-standard on the topic.

This book builds on that with an emphasis on information security is worth a read for those with an interest in the topic.

Syngress 0128002077 978-0128002070 Ben Rothke