We apply principles to different phases of big data processing: collection, storage, processing, analysis and visualization. We discuss how to choose the right technology at 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 putting together these technologies to solve your big data problems at the right cost.

Full title: AWS re:Invent 2018: [REPEAT 1] Architecture Patterns and Best Practices for Big Data Analytics (ANT201-R1)

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