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.
Andy Davies, Aaron Peters present how networks, browsers and the way sites are built affect user experience, and take a look at some of the latest techniques for measuring and improving performance.
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.
Rajeev Borborah, Matthew Wilson discuss using NoSQL at WebMD -architecture, benefits, roadmap-, with details on caching and key-value storage implementation behind a few of the WebMD applications: Physician Finder, Symptom Checker and WebMD Runtime.
Sponsored by Twilio. Matt Makai explores why deployments are difficult and shows solutions with case studies on how other organizations cut their production deployment times down from months to hours.
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.
Frank Breedijk addresses security concerns raised in a DevOps environment that practices continuous deployment.
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.
Joe Armstrong describes the foundations of fault tolerant computation and the basic properties a system should have in order to be able to function in an adequate manner despite the occurrence of hardware and software errors, summarizing the key features of Erlang and showing how they can be used for programming fault-tolerant and scalable systems on multi-core clusters.