What are the essential components of a data platform? John Akred and Stephen O’Sullivan explain how the various parts of the Hadoop, Spark, and big data ecosystems 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, John and Stephen explore the options and considerations for components, including acquisition from internal and external data sources, ingestion (offline and real-time processing), storage, analytics (batch and interactive), and providing data services (exposing data to applications). They’ll also give advice on tool selection, the function of the major Hadoop components and other big data technologies such as Spark and Kafka, and 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. As CTO of Silicon Valley Data Science, John 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 has 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 at Silicon Valley Data Science.
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