Using Cooperative Analytic Processing to Unleash Your Analytics
Paige Roberts
The ability to do complex ad-hoc queries and analytics at scale is a Big Data dream that many are talking about, but very few are actually achieving. SMBs are stifled by budget, while the companies who have invested in trendy new in-memory databases are settling for hours or sometimes day-long queries in order to get the answers they want from their data. This could hardly be considered "ad-hoc." It would be easy to assume that we simply don't have access to the technology to unlock this vision yet, but that would be incorrect.

Cooperative Analytic Processing is an analytics technique designed to make the most out of your entire Hadoop ecosystem, driven by the principle that the processing should be with the most appropriate tools available as close to the data as possible. Companies are successfully utilizing Cooperative Analytic Processing to get their analysts time on the system so that they can produce business value.

In this class, you will be given a summary of the underlying principles that drive Cooperative Analytic Processing, as well as a short overview of its successful implementations and benefits. You will then be shown in-depth samples of how to successfully move processes closer to data in order to speed analytic queries for their own organization.

Level : Advanced