Ian Robinson takes a look at how size, structure and connectedness have converged to change the way we work with data, showing some new opportunities with connected data illustrated with graph search.
Volker Pacher, Sam Phillips present key differences between relational databases and graph databases, and how they use the later to model a complex domain and to gain insights into their data.
Justin Moore shares how Facebook's own advances in Data Science have solved intricate location technology problems and how these lessons can be applied to other verticals to achieve similar gains.
Simon Redfern presents how the Open Bank Project innovates by leveraging open APIs, open source and open data, making banking data more accessible via an ecosystem of apps and services.
Alvaro Videla shows how to build a system that can ingest data produced at separate locations and replicate it across regions using RabbitMQ.
Sponsored by Basho. Sean Cribbs discusses the theory behind several rich data types introduced with Riak 2.0 and then walking through some example applications that use them in popular languages.
Chris Risner demos an Android app built with Azure Mobile Services using structured data stored in the cloud, GCM push notifications with a single line of code, authentication, security and others.
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 Solace Systems, Aaron Lee discusses the challenges moving information and techniques that can increase efficiency of data flows within big data architectures
In this solutions track talk, sponsored by Neo Technology, Ian Robinson takes a look at how size, structure and connectivity have converged to transform the data landscape.
Nathan Marz discusses building NoSQL-based data systems that are scalable and easy to reason about.
Chris Mattmann envisions data science by integrating science software into rapid data production systems using cloud computing and open source software.