Garrett Eardley explores how Riot Games is using Riak for their stats system, discussing why they chose Riak, the data model and indexes, and strategies for working with eventually consistent data.
Ronny Kohavi shares lessons learned, cultural and scaling challenges conducting hundreds of concurrent online controlled experiments at Bing.
Jonathan Seidman and Ramesh Venkataramaiah present how they run R on Hadoop in order to perform distributed analysis on large data sets, including some alternatives to their solution.
Nathan Marz explain Storm, a distributed fault-tolerant and real-time computational system currently used by Twitter to keep statistics on user clicks for every URL and domain.
Hilary Mason presents the history of machine learning covering the most significant developments in the area, and showing how bit.ly uses it to discover various statistical information about users.