Nellwyn Thomas discusses how Etsy is using A/B testing, how Etsy's data-driven culture has evolved over time and how continuous delivery and big data can coexist.
Shawn Gandhi provides an overview of the key scenarios and business use cases suitable for real-time processing, and how developers are using AWS Kinesis to shift from a traditional batch-oriented approach to a continual real-time data processing model.
Randy Shoup describes KIXEYE's analytics infrastructure from Kafka queues through Hadoop 2 to Hive and Redshift, built for flexibility, experimentation, iteration, componentization, testability, reliability and replay-ability.
Marcel Kornacker presents a case study of an EDW built on Impala running on 45 nodes, reducing processing time from hours to seconds and consolidating multiple data sets into one single view.
In this solutions track talk, sponsored by Cloudera, Eva Andreasson discusses how search and Hadoop can help with some of the industry's biggest challenges. She introduces the data hub concept.
In this solutions track talk, sponsored by MongoDB, Matt Asay discusses the differences and tradeoffs between some of the NoSQL and SQL databases and when Hadoop makes sense to be used with a NoSQL solution.
In this solutions track talk, sponsored by Solace Systems, Aaron Lee discusses the value and challenges of efficiently moving information along with techniques and tools that can increase the rate and efficiency of data flows within big data architectures.
Gunter Dueck wonders how are we preparing for the new society marked by cloud computing and big data in which jobs are automated and mediocre abilities are no longer accepted?
Chris Mattmann covers four critical areas emerging in the context of NASA projects in radio astronomy; in snow hydrology and regional climate modeling; climate science, and in intelligence activities that together we must significantly advance to deal with the data deluge across NASA and government agencies.
Akmal B. Chaudhri introduces Apache™ Hadoop® 2.0 and Yet Another Resource Negotiator (YARN).
Eva Andreasson presents typical categories of problems that are commonly solved using Hadoop and also some concrete examples in each category.