Archiving and big data analytics: where to put all the data – Randy Kerns blog on Storage Soup

There are many opinions regarding how to handle information storage for big data analytics. By big data analytics,  I’m referring to information associated with a data analytics operation that does the analysis in near real-time to present immediately actionable results. The most common approach to this type of analysis is to provide data that is the source for the real-time analytics process to the compute nodes with minimal latency and at a high data rate.

This requirement has led many data scientists designing analytics systems to require –Click Here to read the rest of Randy’s Storage Soup blog.