In this session, we discuss architectural principles that helps simplify big data analytics. We'll apply principles to various stages of big data processing: collect, store, process, analyze, and visualize. We'll disucss 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. Finall
![Big Data Analytics Architectural Patterns and Best Practices (ANT201-R1) - AWS re:Invent 2018](https://cdn-ak-scissors.b.st-hatena.com/image/square/7b1813336d7fea2a53865bbd80302e098371cdf1/height=288;version=1;width=512/https%3A%2F%2Fcdn.slidesharecdn.com%2Fss_thumbnails%2Fbig-data-analytics-architectur-295f8bd0-1754-4507-8d1b-c7ce421497db-71661062-181127201528-thumbnail.jpg%3Fwidth%3D640%26height%3D640%26fit%3Dbounds)