Two common use cases for data warehousing are:
- You want to generate reports from historical data without impacting transactional processing.
- You want to provide a platform for data mining.
Data warehousing lets you consolidate data from multiple sources for analysis and reporting.
Data stores are optimized for read operations with few, if any, writes performed on the data.
There are typically no locking requirements in a data warehouse.
You are not consolidating data into a non-relational store. Azure data warehousing solutions use relational data with a schema strongly enforced on data load and write. Data is sometimes less normalized in a data warehousing solution than data for transaction processing. The complex queries and analysis in data warehousing is often better suited to less normalized data.
You would not use a data warehousing solution for a widely distributed transactional processing application. This requires a data solution optimized for write operations that provides for data locking and strong consistency.