High Performance Analytics first. As already noted this is a key focus area for SAS. The three pillars, remember, are:
- Grid Computing
Allocating out analytic tasks to multiple processors and cores in a managed fashion.
- In-Database Analytics
Using database servers for analytic computing to minimize data movement and improve performance.
- In-Memory Analytics
The key area in many ways for highest end problems. Consists of SAS High Performance Analytics, SAS High Performance Solutions and SAS Visual Analytics.
Fundamentally to solve performance problems you must improve the execution of the algorithms involved AND the management of large amounts of data (big data). In particular companies don’t want to have to sample data before processing it. They also want to do more granular analytics, focusing on transaction detail not just account detail for instance. The purpose of the high performance analytics effort at SAS is to allow more sophisticated, more interesting analytics against more data, big data so there is no need to dumb down the analysis due to the volume of data. They want to ensure that big data won’t break the current analytics approaches and tools in use by customers (such as existing SAS scripts and models) and that even more advanced analytics can be done against these new data volumes.