February 12, 2014

Operational Business Intelligence for the Reactive Enterprise

We are in a day and age where infrastructure, and to some extent, businesses, are moving towards reactive IT instead of traditional proactive IT. Why reactive IT? Think auto-scaling vs traditional capacity planning for instance. Or the move towards schema-less NoSQL instead of traditional RDBMS. All in all, reactive IT enables an enterprise and its infrastructure to react to its internal and external environment. In order to achieve this, a real-time, or near real time, event driven model is a must –  agents to pull/push streams of events, systems to process these events quickly and efficiently and the ability to use these processed events to react.

Operational Business Intelligence (knowns as OBI or operational BI) or Operational Intelligence is defined as the analysis of operational data and information in an enterprise – this deals with the real time or low latency analysis of streaming events or batched enterprise data providing feedback in terms of input to the enterprise. OI provides organisations with real time insights into enterprise operations, providing organisations the ability to act upon, or in other words react, to events – enabling organisations to ‘listen’ to and process events as they come in, detect anomalies and patterns, and take reactive measures.

Of course, with large amounts of data come big challenges, and with big challenges come big data. With the possibility of dealing with massive data sets within OI, big data concepts have started becoming a mainstay in organisational OI. Modern OI solutions have started focusing on large NoSQL data stores possibly processed in batch mode and streaming events.

OI would provide a unified, correlated view of streaming big data, processed big data, complex events and processes, with the ability to analyse, mine and process data and information – a prerequisite to building a reactive enterprise. Enterprise users and devops have come to expect the following kind of information from a unified OI view

  • Analysis of information, and mining for patterns
  • Adhoc, real time dashboards
  • Adhoc search of patterns across the enterprise
  • Alerting based on event occurences
  • Monitoring of system health, load, KPIs


OI has many technology components, often with shared feature sets. Some of the notable solutions are

  • Business Activity Monitoring (BAM) – Monitoring of activities and events, usually batch processed and provided via dashboards. Used to track  KPIs related to activities and performance.
  • Complex Event Processing (CEP) – Processing of a continuous stream of events, usually in-memory. High performance with the ability to detect certain patterns and anomalies in the incoming streams.
  • Business Process Management (BPM) – Model driven execution of processes and policies, including business workflows with human intervention.

Independently the above components handle a very specific area of OI, and together they provide the building blocks for a comprehensive and unified OI.

In a later post, we will explore how the WSO2 stack, a comprehensive Open Source middleware stack, can be utilised for Operational Intelligence in an enterprise.


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