Applications & Data · Analytics
Data Warehousing
Consolidating data from operational systems into a modelled, query optimised store for analysis and reporting.
IntermediateUpdated 2026-09-01
Overview
A warehouse ingests from source systems on a schedule or stream, transforms into a dimensional or wide model, and serves analytical queries efficiently. ELT patterns now dominate: load raw data first, transform inside the warehouse.
The lakehouse pattern merges warehouse and lake, keeping open format files in object storage with a table layer that provides transactions and schema evolution.
Security considerations
- Apply row- and column level security so analytical access does not become a data-exfiltration path.
- Track lineage so figures in reports can be traced to their source system.