You now have a deeper overview of the SAS platform and learned that SAS programming skills can easily be applied to doing big data analytics, because the coding stays relatively the same when using SAS on any size of data. However, when working on big data, it's the SAS environment that must be set up and configured properly in order for the processing to return results in a timely manner.
You saw how SAS enables processing on a server, on a SAS grid, in a database, and in memory as a way to reduce data movement or duplication, as well as enable the capability to do analytics on big data.
In addition, you learned how the SAS platform is open and how SAS integrates and works with open source technologies. You gained some hands-on experience using SAS with the open-source-based iPython Jupyter Notebook.
You learned about the different cloud environments and deployments in which SAS technologies are designed to integrate with open source in order to provide an enterprise analytics platform...