I started with a star schema, trips as the fact table, dimensions for drivers, riders, locations, time.
Start by clarifying the business goals and key metrics (e.g., trip analysis, driver performance, pricing) to determine the required facts and dimensions. Then propose a dimensional model (star schema) with a central fact table for trips and supporting dimensions, explaining how it supports analytical queries. Finally, discuss trade-offs like normalization vs. denormalization, partitioning, and scalability.
Pro tip: Emphasize that the schema should be optimized for query performance and scalability, and mention how you would handle slowly changing dimensions (SCDs) for entities like drivers and riders to maintain historical accuracy.
Ask about the key business questions and metrics (e.g., trip counts, revenue, driver utilization) to ensure the schema supports them.
Determine the central fact table (e.g., trips) and the dimensions (e.g., time, location, driver, rider, payment) that provide context.
Propose a star schema with a fact table containing foreign keys to dimensions and additive measures like fare and distance.
Explain how to handle changes in dimension attributes (e.g., driver's rating) using SCD Type 2 to preserve history.
Talk about partitioning the fact table by date, indexing strategies, and potential use of columnar storage for performance.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.