Neha Narkhede discusses how companies are using Apache Kafka and where it fits in the Big Data ecosystem.
Matt Zimmer discusses architectural patterns -service decomposition, stateless application tiers, and polyglot persistence- and migration strategies used by Netflix.
Vaclav Petricek discusses how to train models, architect and build a scalable system powered by Storm, Hadoop, Spark, Spring Boot and Vowpal Wabbit that meets SLAs measured in tens of milliseconds.
Christopher Meiklejohn looks at applying two techniques together, deterministic data flow programming and conflict-free replicated data types, to create highly available and fault-tolerant systems.
Mandy Waite shows how to get started with Firebase before walking through a live demo of building a multi-user, collaborative mobile app that provides real-time updates to its users.
Julien Lavigne du Cadet discusses how Criteo uses Druid: an open-source, real-time data store designed to power interactive applications at scale, covering Druid's architecture and internals.
Mini-talks: The Machine Intelligence Landscape: A Venture Capital Perspective. The future of global, trustless transactions on the largest graph: blockchain. Algorithms for Anti-Money Laundering
Mini-talks on: OS/application inversion, testing, living databases, and rogue protocols.
Ben Christensen discusses the mental shift from imperative to declarative programming, working with blocking IO such as JDBC and RPC, service composition, debugging and unit testing.
Sandy Ryza aims to give a feel for what it is like to approach financial modeling with modern big data tools, using the Monte Carlo method for a a basic VaR calculation with Spark.
Howard Chu covers highlights of the LMDB design and discusses some of the internal improvements in slapd due to LMDB, as well as the impact of LMDB on other projects.
Chris Matts discusses how to manage product mastery, how do we decide whether to use analysis or product management techniques, and what does an end-to-end process looks like.