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The Larger Purpose of Big Data with Pavlo Baron

Posted by Pavlo Baron on  Jan 30, 2013

Big Data means more than just the size of a dataset. Pavlo Baron explains different ways of applying Big Data concepts in various situations: from analytics, to delivering content, to medical applications. His larger vision for Big Data ranges from specialized Data Scientists, to learning Decision Support Systems, to helping mankind itself.

Erik Meijer on Big Data, Types of Data Stores and Reactive Programming

Posted by Erik Meijer on  Jan 04, 2013 1

Erik Meijer explains the various aspects needed to categorise data stores, how reactive programming fits in with databases, the return to data transformation, denotational semantics, and much more.

Eli Collins on Hadoop

Posted by Eli Collins on  Aug 17, 2012

Eli Collins discusses Cloudera's CDH4 release, which tasks are well suited for Hadoop, Hadoop and MapReduce vs SQL, the state of Hadoop, and much more.

Stuart Halloway on Datomic, Clojure, Reducers

Posted by Stuart Halloway on  Aug 15, 2012

Stuart Halloway explains Datomic, programming transactional behavior with Datomic, Datalog and logic programming, programming with values, Clojure Reducers and much more.

Max Sklar on Machine Learning at Foursquare

Posted by Max Sklar on  Aug 09, 2012

Max Sklar talks about machine learning at Foursquare, the use of Bayesian Statistics and other methods to build Foursquare's recommendation system and much more.

Big Data Architecture at LinkedIn

Posted by Siddharth Anand on  May 14, 2012 1

In this interview at QCon London, LinkedIn’s Sid Anand discusses the problems they face when serving high-traffic, high-volume data. Sid explains how they’re moving some use cases from Oracle to gain headroom, and lifts the hood on their open source search and data replication projects, including Kafka, Voldemort, Espresso and Databus.

Hadoop and NoSQL in a Big Data Environment

Posted by Ron Bodkin on  Feb 03, 2012

Ron Bodkin of Big Data Analytics discusses early adoption of Hadoop, NoSQL and big data technologies. He discusses common patterns and explains how developers can write low-level primitives to optimize MapReduce function. Other topics include Hive, Pig, multi tenancy, and security.

All things Hadoop

Posted by Ted Dunning on  Feb 02, 2012 2

In this interview Ted Dunning talk about Hadoop, its current usage and its future. He explains the reasons for Hadoop's success and make recommendations on how to start using it.

Costin Leau on Spring Data, Spring Hadoop and Data Grid Patterns

Posted by Costin Leau on  Nov 23, 2011 4

In this interview recorded at JavaOne 2011 Conference, Spring Hadoop project lead Costin Leau talks about the current state and upcoming features of Spring Data and Spring Hadoop projects. He also talks about the Caching and Data Grid architecture patterns.

Ville Tuulos on Big Data and Map/Reduce in Erlang and Python with Disco

Posted by Ville Tuulos on  Jun 24, 2011

Ville Tuulos talks about Disco, the Map/Reduce framework for Python and Erlang, real-world data mining with Python, the advantages of Erlang for distributed and fault tolerant software, and more.

Rob Pike on Parallelism and Concurrency in Programming Languages

Posted by Rob Pike on  Feb 17, 2011 3

Rob Pike discusses concurrency in programming languages: CSP, channels, the role of coroutines, Plan 9, MapReduce and Sawzall, processes vs threads in Unix, and more programming language history.

Ron Bodkin on Big Data and Analytics

Posted by Ron Bodkin on  Jan 27, 2011

Ron Bodkin discusses big data architecture, real-time analytics, batch processing, map-reduce, and data science.

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