Real-Time Product Intelligence for Governed Decisions
DOI:
https://doi.org/10.5281/0vz8b874Keywords:
Event-Driven Product Intelligence, Continuous Governance, Decision Optimization, Data Structures for Governance, Data-Enabled Decision-Making, Topology Awareness, Event Taxonomy,Event-Driven Architecture Product Intelligence,Continuous Governance,Enterprise Decision Optimization,Real-Time Event Processing,Complex Event Processing (CEP),AI-Driven Decision Support,Intelligent Business Analytics,Enterprise Data Governance,Predictive Decision Intelligence.Abstract
Event-driven product intelligence and its application to enterprise governance and decision processes is fundamentally important for events: for their ingestion, modeling, real-time analytics and signaling, control frameworks and implementations across industries. Enterprises are highly dependent on the provenance and the quality of their product intelligence data. Properly constructed events establish the basis for full traceability and product intelligence, two cornerstones required for the continuous governance of enterprise-wide processes, products and systems and defining the quality of the final business decisions. The source data must provide an accurate picture of the enterprise product, service or system ecosystem, covering not only the changes of the elements taken into consideration (features, incidents and so forth) but also the context they occur in (related events) as well as the impact they may have on other domains outside their own (dependencies, escalation paths, business policies). The complete domain picture then feeds streaming analytics procedures capable of detecting and signalling critical situations (anomalies, risk indicators), allowing decision makers to act in a timely and informed manner. Depending on the particular signal produced, a series of predefined actions and escalation paths may guide the decision-making process, both for incidents requiring human intervention and those easily automatable.
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