**Fact properties**: Additive/semi-additive measures; clear grain; FKs to dims; time-series; often partitioned. **Dimension properties**: Descriptive; SCD Type 1 or 2; role-playing (same dim, different roles). **Grain is critical**: One row per order vs. per line-item =...
This medium-level SQL question appears frequently in data engineering interviews at companies like Nagarro. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (partition) will help you answer variations of this question confidently.
Break this problem into components. Identify the core trade-offs involved, then walk the interviewer through your reasoning step by step. Demonstrate awareness of edge cases and production considerations - this is what separates good answers from great ones.
Fact properties: Additive/semi-additive measures; clear grain; FKs to dims; time-series; often partitioned. Dimension properties: Descriptive; SCD Type 1 or 2; role-playing (same dim, different roles). Grain is critical: One row per order vs. per line-item = different measures. Trade-off: Mixed grain in one fact = wrong aggregations. Role-playing dim_date for order_date, ship_date avoids duplicate dimension tables.
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Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.