Real-time business activity monitoring and analysis of process performance on big-data domains

Timely access to performance data is essential to optimise business processes.We introduce a cloud-based infrastructure that monitors process performance in real-time on big data environments.We propose an event correlation algorithm that links a massive number of consecutive events.We demonstrate that our IT solution is able to generate metrics at very low latency rates using low hardware costs. Real-time access to business performance information is critical for corporations to run a competitive business and respond to a continuously changing business environment with ever-higher levels of competition. The timely analysis and monitoring of business processes are essential to identify non-compliant situations and react immediately to those inconsistencies in order to respond quickly to competitors. In this regard, the integration of business intelligence (BI) systems with Process Aware Information Systems (PAIS) can become a key tool for business users in decision making. However, current BI systems are not suitable for optimising and improving end-to-end processes since these are normally business domain specific and are not sufficiently process-aware to support the needs of process improvement type activities. In addition, highly transactional business environments may produce vast amounts of event data that cannot be efficiently managed by the use of traditional storage systems which are not designed to manage vast amounts of event data. We introduce a cloud-based architecture that leverages big-data technology to support performance analysis on any business domain, in a timely manner and regardless of the underlying concerns of the operational systems. Likewise, we demonstrate the ability of the solution to provide real-time business activity monitoring on big-data environments with low hardware costs.