April 2021 Summaries

Operational intelligence, a rapidly emerging analytics category, is driven by the need for real-time decision-making in industries like retail, social media, transportation, and finance, using technologies that process operational event streams to deliver timely insights. Unlike traditional business intelligence, which supports complex decisions with complete datasets on a periodic basis, operational intelligence requires high-speed data processing and immediate feedback to the edge to facilitate fast, frequent decisions. This requires a distinct technology stack that includes event stream processing, fast OLAP databases, and machine-learning applications, with tools like Kafka, Flink, and Apache Druid playing crucial roles. As businesses increasingly leverage ubiquitous computing and a global digital nervous system of connected devices, operational intelligence is poised to expand significantly, although it demands new architectures to meet its unique performance requirements. While the synergies between operational and business intelligence can enhance both, especially in terms of performance and cost efficiencies, the future of data infrastructure may see further integration or continued divergence between these two paradigms.