Intelligent data processing does something different. It observes patterns, draws inferences, adapts to conditions that were not explicitly anticipated, and produces outputs that improve over time.

Latency in the context of big data business intelligence is not simply about how quickly a query returns. It is about the end-to-end delay between a real-world event and the moment that event is reflected in a decision-ready format.

The BI and data warehousing lifecycle is conventionally described in five stages: data ingestion, data transformation, storage and modelling, reporting and analysis, and governance. In practice, most organisations manage to execute the first three reasonably well. The last two, governance and sustainable reporting, are where the lifecycle quietly collapses.