Flexibility of SAS Enterprise Miner

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analyticsClassDo you use an array of tools to perform predictive analytics on your data? Is your current tool not flexible enough to accommodate some of your requirements? SAS Enterprise Miner may be your solution.

With growing number of data mining applications, having a tool which can do variety of analysis is just not enough. Some situations require an open extensible design that provides ultimate flexibility and personalization so that users can tailor their experience according to their needs.

The flexible architecture of SAS Enterprise Miner opens an entire world of SAS to data miners and data scientists with a variety of skill levels, ranging from business users to technical experts.

What can users achieve by SAS Enterprise Miner’s flexible architecture?

When there are situations where you want to customize the functionality based on the business requirements, the SAS code node and extension node come to your rescue. SAS Enterprise Miner’s SAS code node enables users to incorporate new or existing SAS code into the process flow. SAS code node extends the functionality of SAS Enterprise Miner by making SAS procedures available in data mining analysis. One can also create custom extension nodes using SAS code and XML logic and share it with others across the enterprise. Diagrams can be shared easily with other analysts throughout the enterprise.

SAS Enterprise Miner users can exploit the integrated graphic capabilities in their custom SAS code by using macros that come with SAS Enterprise Miner. Using these macros as a part of SAS code node, a user can effectively enhance their graphic layout of the results. SAS Enterprise Miner users can create stored processes for business users who can easily run data mining algorithms from their choice of environment, such as the Microsoft Excel interface.

And now using the Open Source Integration node, you can run statements and programs from the R language inside an SAS Enterprise Miner workflow.

Users can quickly build creative, highly scalable and reusable solutions in fast-growing analytics world using SAS Enterprise Miner.

For more on this topic, attend the pre-conference workshop, Flexibility of SAS® Enterprise Miner™ at the Analytics 2015 conference in Las Vegas on Sunday, October 25, 2015, 1-5 pm.

Hope to see you there!

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About Author

Anuja Nagpal

Machine Learning Developer, SAS R&D, Advanced Analytics

Anuja Nagpal is a Machine Learning Developer in the Advanced Analytics division of SAS R&D. Her main focus is Machine Learning Pipeline automation. Previously, she worked as an analytical consultant at SAS helping customers solve their business problems by applying machine learning algorithms and statistical modeling techniques in various industries.

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