Design a data warehouse model for tracking feature adoption
This tests your grasp of data warehousing star schemas for efficient behavioral analysis. A strong answer proposes a central `events` fact table linked to `users`, `features`, and `time` dimension tables.
This tests your ability to design an efficient data warehouse schema for analytical queries. A strong answer outlines a star schema: a central `events` fact table (with user_id, feature_id, timestamp) linked to dimension tables for `users`, `features`, and `time`. This structure makes cohort queries fast and scalable. A red flag is proposing a transactional OLTP model or a single, massive denormalized table, which are slow for these analytics and difficult to maintain.
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- #data warehouse
- #sql
- #analytics
- #star schema
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