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.

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.