Personal Reading List: 2Q2016
My personal reading list for April, May, and June 2016.
Color Key: Special Notes, Completed Reading. Updated throughout the Quarter.
At Bat (Schnell)
Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst, by Dean Abbott, Wiley, 2014. Copy provided by Amazon.
Common Errors in Statistics and How to Avoid Them (Fourth Edition), by Phillip I. Good and James W. Hardin, Wiley, 2012.
At Bat (Langsam)
On Deck
Architecting Data Lakes: Data Management Architectures for Advanced Business Use Cases, by Alice LaPlante and Ben Sharma, O'Reilly, 2016. Copy provided by O'Reilly.
Going Pro in Data Science: What it Takes to Succeed as a Professional Data Scientist, by Jerry Overton, O'Reilly, 2016. Copy provided by O'Reilly.
Graph Databases: New Opportunities for Connected Data (Second Edition), by Ian Robinson, Jim Webber, and Emil Eifrem, 2015. Copy provided by Neo4j.
Hadoop Application Architectures: Designing Real World Big Data Applications, by Mark Grover, Ted Malaska, Jonathan Seidman, and Gwen Shapira, O'Reilly, 2015. Copy provided by O'Reilly.
The Hadoop Performance Myth: Why Best Practices Lead to Underutilized Clusters, and Which New Tools Can Help, by Courtney Webster, O'Reilly, 2016. Copy provided by Pepperdata.
Reactive Microservices Architecture: Design Principles for Distributed Systems, by Jonas Bonér, O'Reilly, 2016. Copy provided by O'Reilly.
Real-World Hadoop, by Ted Dunning and Ellen Friedman, O'Reilly, 2015. Copy provided by O'Reilly.
In the Hole
A Little Riak Book 2.0, by Eric Redmond and John Daily, Basho, 2014. Copy provided at Strange Loop 2014 by Craig Vitter, solutions architect at Basho Technologies.