Com­plex Event Processing

Before we jump into Com­plex Event Pro­cessing (CEP), let us first talk about Simple Event Pro­cessing (SEP). Ima­gine a sys­tem where we have an applic­a­tion that pro­cesses data (events) gen­er­ated from another sys­tem, and then cre­ates some out­put as a response. A very basic example could be as fol­lows. You take out a cal­cu­lator and tap in 2+3. For the cal­cu­lator, the input data is the addi­tion of two num­bers i.e. 2, 3. The cal­cu­lator pro­cesses it and gives an answer of 5, which is shown as the response. So, in a nut­shell, Simple Event Pro­cessing ana­lyses and trig­gers actions based on a single event that occurs in an upstream sys­tem. Nat­ur­ally, SEP can be much more com­plex in real-world applications.

Now let’s go over Com­plex Event Pro­cessing (CEP). CEP allows for pat­tern recog­ni­tion and trig­ger­ing actions based on a com­bin­a­tion (pat­tern) of mul­tiple events of dif­fer­ent types and com­ing from dif­fer­ent sources. CEP as a concept was coined in the first half of the 1990s when big enter­prises iden­ti­fied the need for pro­cessing mul­tiple events from a vari­ety of sources sim­ul­tan­eously and cre­at­ing a valu­able insight out of the same. CEP is a clas­sic example of Event-Based Archi­tec­ture. The idea is to pro­cess a stream of events com­ing from dif­fer­ent source sys­tems in real-time and to come up with mean­ing­ful and action­able insight as soon as pos­sible. Like in any other form of data pro­cessing, CEP works on a col­lec­tion of inform­a­tion from vari­ous sources and then pro­cesses them in order to give insight. This allows one to take appro­pri­ate actions. The heart of the entire pro­cess lies in pro­cessing the inbound events with pre­set busi­ness matrices and rules.

The illus­tra­tion below gives an idea of how a CEP sys­tem might look.

CEP pro­cesses incom­ing events based on an exist­ing pat­tern, in a real-time fash­ion. In com­par­ison to Simple Event Pro­cessing, CEP sys­tems execute data manip­u­la­tion on via an algorithm that is pre-stored. The pro­cess achieves speed by dis­card­ing any irrel­ev­ant data in the begin­ning. As soon as the incom­ing events are com­pared to all the stored pat­terns, the result/response is sent out straight away, giv­ing the pro­cess real-time cap­ab­il­it­ies. CEP is used for highly demand­ing, con­tinu­ous-intel­li­gence applic­a­tions that enhance situ­ational aware­ness and sup­port real-time decisions. In addi­tion to this speed, CEP sys­tems are also highly scal­able and per­form­ance-ori­ented. This allows them to cre­ate an insight­ful response in real-time.

CEP has a wide vari­ety of applic­a­tions in vari­ous indus­tries. For example, in the Tele­com industry, CEP can help oper­at­ors under­stand the dynamic needs of their cus­tom­ers on a real-time basis. Let’s explore this example more to under­stand CEP. If a Tele­com oper­ator knows details about its cus­tom­ers (such as their spend­ing capa­city, brand pref­er­ences, loc­a­tion, usage pat­terns, avail­able park­ing slots at a nearby park­ing lot, etc.) then they can send offers per­tain­ing to a given brand when the cus­tomer is near that brand’s store. This type of mar­ket­ing would make more sense when the cus­tomer is near the store, rather than after 1 hour (when the cus­tomer may be miles away from the store). So, the key ele­ments of CEP are the vari­ety and velo­city of pro­cessing the data, allow­ing for real-time actions based on the output.

There are vari­ous open-source and pro­pri­ety tools that can help in pro­cessing com­plex events like Apache Spark, Flink, Samza, etc from the open-source world and power­ful data pro­cessing tools like Ab Ini­tio, Microsoft Azure Stream Ana­lyt­ics, Stream Insight from the pro­pri­ety soft­ware space. How­ever, key factors like per­form­ance, scalab­il­ity, built-in integ­ra­tion cap­ab­il­it­ies, shorter time-to-mar­ket, sup­port of enter­prise require­ments and vendor sup­port with defined SLAs and massively par­al­lel pro­cessing cap­ab­il­it­ies from pro­pri­ety tools can eas­ily out­cast open-source tools.

Ab Ini­tio data plat­form provides fea­tures like a cus­tom build CEP applic­a­tions and out-of-the-box Cus­tomer Inter­ac­tion Plat­form (CIP) that can help organ­iz­a­tions on their com­plex event pro­cessing require­ments with all the above-men­tioned advant­ages of pro­pri­ety tools. With a com­bin­a­tion of other tools from Ab Ini­tio suite like Metadata Hub, Acquire> It, Busi­ness Rule Engine, enter­prises can have enrich­ing fea­tures like end-to-end lin­eage, organ­iz­a­tion-level busi­ness gloss­ar­ies, flex­ible con­trol on trans­form­a­tion rules and the ease of plug and play should there be a require­ment to integ­rate new source systems.

Data Insights as a tech­no­logy part­ner with Ab Ini­tio and the only part­ner in Europe to sup­port CIP can help in cre­at­ing high per­form­ant, real­time event pro­cessing plat­forms for big enter­prises. Get in touch with us to under­stand how our expert­ise can help your organ­iz­a­tion to solve your busi­ness chal­lenges by lever­aging the value of your data to the fullest.