Design a data model for tracking feature adoption
This tests your grasp of data warehouse star schemas for analytics. Outline a fact table for events and dimension tables for users and features, explaining how this structure enables fast, ad-hoc cohort analysis for a product manager.
This question tests your ability to design a data warehouse schema (specifically a star schema) optimized for analytical queries. A great answer proposes a central `fact_events` table linked to `dim_users` and `dim_features` dimension tables, explaining how this structure makes cohort analysis fast. A common red flag is designing a normalized OLTP schema, which is too slow for typical product analytics queries.
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- #analytics
- #sql
- #system design
- #data warehouse
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