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Database problems involving activity analysis and role transitions are common in data-focused interviews. Variants of this problem appear in interviews that test SQL proficiency, analytics thinking, and understanding of relational data patterns.
The optimal approach generally uses SQL joins combined with aggregation or window functions. By linking viewing records with streaming records and grouping by user, you can identify users who appear in both roles and verify the correct transition conditions.
Key SQL concepts include JOIN operations, GROUP BY with HAVING filters, and window functions such as ROW_NUMBER or MIN over partitions. These tools help analyze user activity across multiple records and determine role changes over time.
In database terms, indexed tables keyed by user IDs act like efficient lookup structures. Indexes on user identifiers and timestamps allow joins and aggregations to run faster when scanning large activity logs.