Evolving Patterns in Big Data – Neil Avery, Excelian

Big Data is now the mainstay for many industries. We are seeing typical patterns of use evolving to a point where the gap between vendor and use-case is so repeatable that turn-key solutions are viable.

Utilizing tools like Docker, Ansible and Vagrant vendors are turning to open-source communities to drive big-data to become a low-friction, commodities solution in many industries. This talk explores these patterns and use cases and theorizes about where big data is headed. Data-Lakes, Enterprise Caches, Actors and other Lambda based patterns provide an exciting backdrop to the near future of big data patterns in many industries.

About Neil Avery

Neil has a long history in large scale, distributed computing, ranging from architecting large scale risk-analytic systems, running startups, to data-heavy weather analysis using data-grids. He is a certified Datastax Solution Architect with Cassandra, Spark and Solr and was previously a Principle Architect at Thoughtworks where he lead several large scale projects in Retail, Logistic and other interesting fields.