Building analytics applications requires more than just one good service. It requires the ability to capture a vast amount of data, and react to data changes in real time. It requires flexible tools that enable end users to work in the way they can be most productive, and that address the needs of both data consumers and data scientists. This analysis won't just be about data exploration and reports, but must be able to support the largest, most complex machine and deep learning models imaginable. Across it all, strong governance, security, and cataloguing is essential.

In this session, we'll show how to assemble a full stack analytics capability using AWS services. We'll see how to capture static and dynamic data in real time, and react to data changes. We'll show how AWS services support analytics activities ranging from drag-and-drop, through simple query-on-files, to exascale data science. And we'll discuss the architectural practices that lay the foundations for your building a platform that will meet the demands of the most sophisticated analytics customers for many years to come.