Without doubt, SAS has the most sophisticated statistical models. However, as data analyitcs practitioners in real business world, we have realized that 80% or more of the time is spent on data preparation and model deployment. Thus, to decide which analytic platform to use in an company, we need to carefully assess factors including how the models will be used (online or offline), the staff's knowlege levels about SAS and SQL, data security, data size, costs, etc.
In my opinion, data should be stored, managed and analyzed in a SQL based database as much as possible. For example, with Oracle 11g, we can perform all the tasks including data collection, summary, manipulation, model building, model scoring, reporting, within a single environment. This in-database analytics approach greatly increases the productivity, manageability and security.
This blog is mostly focused on the technical aspect of data mining.
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