SQL for Business Scenarios Questions

Ability to read and decompose business questions and translate them into correct, efficient Structured Query Language queries that answer those questions. This includes identifying the required data sources and joins, choosing between inner joins, outer joins, anti joins and existence checks, writing subqueries and common table expressions for clarity, and applying filtering with where clauses, aggregation with group by and having, and window functions for ranking, running totals, and time series calculations. Candidates should demonstrate how to implement common business analyses such as conversion funnels, retention and cohort analysis, churn and lifetime value calculations, and operational metrics by mapping metric definitions to SQL expressions and handling edge cases like null values, duplicates, and late arriving data. The description also covers writing medium complexity queries that combine multiple tables, calculating derived metrics, validating results with sample data, and considering query performance through basic optimization techniques, indexing awareness, and selective projection.

EasyTechnical

65 practiced

Rewrite the following multi-step transformation using Common Table Expressions (CTEs) and explain why CTEs improve readability and maintainability: 1) filter active users, 2) compute first_purchase_date per user, 3) join to marketing_campaigns to attribute campaign. Provide the CTE-based SQL and mention performance considerations (materialized vs inline CTE behavior in modern engines).

EasyTechnical

71 practiced

Given raw_events(event_id, user_id, event_type, occurred_at, event_payload JSON) where duplicates exist due to retries, write a SQL query to deduplicate and keep only the latest event per (user_id, event_type, occurred_at_bucket) and insert results into canonical_events. Explain idempotency considerations, how you choose the dedupe key, and how you would run this dedupe incrementally.

HardTechnical

68 practiced

Write SQL to reconcile orders (source A) and billing (source B) and classify mismatches into: missing-in-billing, missing-in-orders, amount-mismatch, duplicate-ids. Provide an example SQL reconciliation report (order_id, status, order_amount, billing_amount, notes) and explain how to scale this comparison for very large tables efficiently.

MediumTechnical

66 practiced

You run daily aggregates from an events table but sometimes receive late-arriving events. Describe a SQL reconciliation strategy that detects historical days whose aggregates changed due to late events and write a sample query that identifies dates where the current aggregate differs from the snapshot used in the previous report.

MediumTechnical

74 practiced

Explain and write SQL to perform an incremental upsert into a dimension table customers(customer_id, name, email, updated_at) from a source table customer_updates with timestamps. Show how to use MERGE (or equivalent) to handle inserts, updates, and soft-deletes, and describe how to support late-arriving updates and idempotent runs.

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