Monday, April 3, 2017
08:30 AM - 11:45 AM
What are the essential components of a data platform? This tutorial will explain how the various parts of the Hadoop, Spark, and big data ecosystem fit together in production to create a data platform supporting batch, interactive, and real-time analytical workloads.
By tracing the flow of data from source to output, we’ll explore the options and considerations for components, including:
- Acquisition: from internal and external data sources
- Ingestion: offline and real-time processing
- Analytics: batch and interactive
- Providing data services: exposing data to applications
We’ll also give advice on:
- Tool selection
- The function of the major Hadoop components and other big data technologies such as Spark and Kafka
- Integration with legacy systems
With over 15 years in advanced analytical applications and architecture, John Akred is dedicated to helping organizations become more data-driven. He combines deep expertise in analytics and data science with business acumen and dynamic engineering leadership.
A leading expert on big data architecture and Hadoop, Stephen O'Sullivan brings over 20 years of experience creating scalable, high-availability data and applications solutions. A veteran of WalmartLabs, Sun, and Yahoo!, Stephen leads data architecture and infrastructure.
Mark Mims has extensive experience architecting and implementing data science solutions across a variety of industries. His passion is Data Plumbing, where Data Science meets the real world of DevOps and Infrastructure Engineering.