Is the SAS Embedded Process a secret sauce for Hadoop?

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SAS has been developing "secret sauce" technology for more than 38 years.  Whether it has to do with being platform independent, processing in-database, running across a grid, or analyzing data in-memory like our SAS LASR Analytic Server or our High Performance Analytics offerings, secret sauce makes everything taste or, in this case, work more efficiently. And, as a result, the SAS secret sauce helps customers be more successful and profitable.

For example, the SAS Embedded Process helped one customer make 1 to 2 million dollars more a month. How on earth could technology make that big of a difference? Because this technology optimized a critical business process that targeted a subset of customers who are most likely to pay their debts. Before, this required a manual, 300-step process over 6 months to create, validate and deploy a predictive model into production. Now, this process has been streamlined into a 10-step, automated, 2-week process that works on all the organization's customers (instead of a small subset), making their collection efforts more effective and efficient.

So, what is the SAS Embed Process? You can think of it as the next phase in SAS' original design concept to write code once and run it on different platforms. It is the underlying technology that supports running SAS code in multiple platforms, which ultimately means less data movement and faster data processing, because you can easily move the analytical data prep, model development, and model execution to where the data resides.

If you've been reading this blog closely, you know that SAS works with data stored in Hadoop in three distinct ways: FROM, WITH, and IN. Well, the SAS embedded process is the enabling technology that supports the WITH and IN part of SAS working with Hadoop.

Similar to the SAS LASR Analytic Server, the SAS Embedded Process is NOT a product or offering in and of itself. Rather, it is the technology that allows in-memory and in-database offerings from SAS like the SAS Scoring Accelerator to function. SimilarlySAS Visual Analytics and SAS Visual Statistics are offerings that can't function without the "secret sauce" of the SAS LASR Analytic Server. 

While we can't give away the complete recipe to our secret sauces, we do encourage customers to enjoy them. What I find the most interesting about this particular recipe is that it was originally made to support in-database processing. But our research and development teams continued to expand its capabilities and features to make the majority of the SAS Embedded Process code portable not only across different databases (like Teradata, Pivotal, Oracle, DB2, Netezza) but also across big data platforms like Hadoop and SAP HANA. These types of innovative developments (or secret sauces) are critical for enabling our customers to bring the data from the Intenet of Things to life.

To learn more about the SAS Embedded Process and the SAS language DS2, read the SAS 9.4 DS2 Language Reference. Papers presented at SAS user groups about Parallel Data Preparation with the DS2 Programming Lanaguage are also good resources.

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About Author

David Pope

Technical Leader, Senior Manager US Energy

David leads the pre-sales technical team for SAS US Energy which solves business problems in the Oil & Gas and Utilities industries using advanced analytics. He earned a BS in Industry Engineering and a Computer Programming Certificate from North Carolina State University. Furthermore, he has over 28 years of business experience working with SAS across R&D, IT, Sales and Marketing in the Americas and Europe. He is an expert in working with data and producing insights through the use of analytics. David has presented at SAS Global Forum, the 2012 SAS Government Leadership Summit, IBM’s Information on Demand(IOD), EMC World, CTO Summit Conferences, is the author of the book: "Big Data Analytics with SAS", and he currently holds 14 patents for SAS in several countries: US, CA, Norway, UK, China, Mexico, and Hong Kong.

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