Big Data Analysis Patterns with Hadoop, Mahout and SOLR

  • Jun 27, 2013 · 6:30 PM
  • Bronto Software, Inc.

Big Data Analysis Patterns

Speaker: Brad Anderson, MapR

Date: June 27th, 6:30PM

Location: Bronto Software, Durham, NC


Big Data Analysis Patterns: Tying real world use cases to strategies for analysis using big data technologies and tools.

Big data is ushering in a new era for analytics with large scale data and relatively simple algorithms driving results rather than relying on complex models that use sample data. When you are ready to extract benefits from your data, how do you decide what approach, what algorithm, what tool to use? The answer is simpler than you think.

This session tackles big data analysis with a practical description of strategies for several classes of application types, identified concretely with use cases. Topics include new approaches to search and recommendation using scalable technologies such as Hadoop, Mahout, Storm, Solr, & Titan.


About the Speaker

Brad Anderson has been wrangling data for 20 years, first with enterprise data warehouses and more recently building and using non-relational big data tools. Previously, he worked on a large-scale video-on-demand platform in Erlang, helped Cloudant build its hosted NoSQL offering based on CouchDB, and organized the NoSQL East 2009 conference in Atlanta. He has recently worked with Cascading, Storm and Neo4J, and has contributed code to the HBase open-source project. Brad has founded or co-founded four technology companies, and his first company operates today as Mirus Restaurant Solutions.

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