Big Data Analytics Architectural Patterns & Best Practices

In this session, we discuss architectural principles that help simplify big data analytics.

We’ll apply principles to various stages of big data processing: collect, store, process, analyze, and visualize. We’ll discuss how to choose the right technology in each stage based on criteria such as data structure, query latency, cost, request rate, item size, data volume, durability, and so on.

Finally, we provide reference architectures, design patterns, and best practices for assembling these technologies to solve your big data problems at the right cost.