In the realm of analytics, organizations are now understanding the shortcomings and drawbacks of batch-oriented data processing, it is becoming clear that Stream processing is inevitable in many real-life applications. Stream processing turns the batch oriented computation upside down on its head, latter is store-compute paradigm whereas Stream processing is compute-store i.e perform in real-time operations such as filter, join, enrich, aggregate, group-by before the data or aggregates are stored for historical analysis.
The heart of Vitria OI is the analytics engine, which has been designed and optimized to perform in-memory analytics over real-time streams of data. The Complex Event Processing Analytic Query models, called Event Processing Networks (EPN) are created in a graphical modeling environment that provides a rich library of services and functions that have been optimized to participate in the continuous, real-time analysis and pattern recognition algorithms.
Successful business operations depend on processes – specifically, on repeatable, measurable processes that can be improved and extended over time.