Want real-time predictive analysis? You need Event Stream Processing

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As more and more data is being collected and analyzed, it becomes even more important to have a strategy in place that will allow you to get value out of your data. Since it's humanly impossible for your brain alone to process fast streaming data, an event stream processing (ESP) engine can give you that desired real-time analysis for insight on the fly.

ESP is a system that continuously analyzes data as it flows into the organization, and then triggers actions based on the information flow. Analysts are using it to spot patterns and make decisions faster than ever before.

For ESP to work, you need more than a simple if-then business rule engine (although that is part of it). What's more important is the ability to apply a variety of predictive or prescriptive types of analytics that will "learn" on the fly and update your models in place. A good ESP solution also performs off-stream analysis, which provides a feedback loop into the stream or ESP production "jobs."  The smart grid in utilities and drilling control projects in oil and gas are great examples of where this type of process and technology need to be applied, but it being used in many other industries as well.

Event Stream Processing diagram

How real-time and batch processing work together to process streaming data

My colleague Moray Liang also provides a great ESP example in his recent post, Breathing new life into wellbore surveillance . If you need more advice on gaining insight from complex data or big data, please reach out to SAS via our newly refreshed website or contact us,  and we will be glad to help.

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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 is a lifetime learner who enjoys sharing information and helping others to grow their careers. He earned a BS in Industry Engineering and a Computer Programming Certificate from North Carolina State University. Furthermore, he has over 29 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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