Explain data warehouse purpose and how it differs from OLTP
This tests whether you know the OLTP versus analytics split. A great answer contrasts OLTP row-level writes and normalized schemas with warehouse denormalized schemas and BI reads. A red flag is calling a warehouse just a bigger OLTP database.
This tests your understanding of the operational versus analytical workload split. A strong answer explains that a warehouse centralizes integrated historical data for BI reporting and complex reads, typically using denormalized star schemas. It contrasts this with OLTP systems that prioritize millisecond row-level writes, ACID compliance, and normalized schemas for daily operations. A red flag is claiming a warehouse is just a bigger OLTP database or that they are interchangeable.
Read the original → Wikipedia: Data warehouse
- #data warehouse
- #OLTP
- #analytics
- #database design
- #BI
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