What is a data warehouse vs. a transactional database?
Tests your grasp of read-optimized (OLAP) vs. write-optimized (OLTP) systems. A great answer defines warehouses for analysis, contrasts them with transactional DBs for operations, and explains the resulting differences in workload, schema, and data structure.
This tests your grasp of read-optimized (OLAP) vs. write-optimized (OLTP) system trade-offs. A strong answer defines a data warehouse as a central repository for historical, integrated data used for analysis. Contrast this with an OLTP database designed for fast, real-time transactions. Then, detail the key differences in workload (complex analytical queries vs. simple CRUD), data model (denormalized star schema vs. normalized 3NF), and data itself (historical/aggregated vs. current/atomic).
Read the original → Wikipedia: Data warehouse
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