UC Berkeley School of Information has a great course, where UC Berkeley professors and Twitter engineers are lectureing on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing.
Bill Graham (@billgraham), who is active in the Hadoop community and a Pig contributor, gave a very clear and detailed intro to Hadoop and outlined how it is used at Twitter. His slides can be found here.

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UC Berkeley Course Lectures: Analyzing Big Data with Twitter

Peter Voss – Analyzing Hadoop Source Code with Hadoop from newthinking on Vimeo.

Using Hadoop based business intelligence analytics, we analyzed the Hadoop source code and its development over time and found some interesting and fun facts we want to share with the community. This talk will illustrate text and related analytics with Hadoop on Hadoop to reveal the true hidden secrets of the elephant.
This entertaining session highlights the value of data correlation across multiple datasets and the visualization of those correlations to reveal hidden data relationships.

More Info: berlinbuzzwords.de/sessions/analyzing-hadoop-source-code-hadoop

Nicolas Spiegelberg Facebook from newthinking on Vimeo.

Nicolas Spiegelberg