It’s a common source of confusion. In simple terms:
– Operational databases sit behind your applications and are optimised for fast, transactional reads/writes — not for complex reporting across years of data.
– Data warehouses are optimised for analytics — structured, modelled, fast for aggregations and historical reporting.
– Data lakes store raw, often unstructured data (logs, files, telemetry) at low cost; warehouses sit on top, working with cleaned, modelled data.
– BI tools (Power BI, Tableau, Looker) are the visualisation layer — they read from the warehouse.
Modern designs blend a data lake and warehouse into a “lakehouse” architecture, with BI on top. We choose the right pattern based on your data volume, complexity and budget.