Complex Data Integration and Joins Questions

Handling intricate join scenarios: multi-condition joins, conditional joins with complex logic, joining on date ranges or overlapping time periods, complex left joins with multiple filtering conditions, self-joins for hierarchical or relationship data, handling non-standard relationships between tables. Understanding implications of different join types on row counts, NULL values, and duplicate handling. Designing queries that correctly integrate data from multiple sources while maintaining data integrity and avoiding duplicate counting or missing data.

HardTechnical

43 practiced

You have a dimension using SCD Type 2 and a fact table with event_time. Dimension table:

sql

dim_customer(customer_sk, customer_id, valid_from, valid_to, is_current)
fact_orders(order_id, customer_id, order_time, amount)

Design a join to attach the correct dim_customer.customer_sk to each fact_orders row. Consider inclusive/exclusive boundaries, open-ended validity, and performance.

MediumTechnical

43 practiced

You must join two tables where one side is highly duplicated (e.g., products with many tags) and the other is moderate size. Describe strategies to avoid row explosion and improve performance: pre-aggregation, DISTINCT on keys, semi-joins, or materialized intermediate tables. Provide SQL sketch for pre-aggregation approach.

MediumTechnical

62 practiced

You have two tables with many-to-many relationships causing multiplicative rows when joined. Describe a step-by-step approach to produce a de-duplicated report of counts per dimension without over-counting. Include SQL patterns (subqueries/CTEs/aggregation order) and why order matters.

MediumTechnical

41 practiced

A report requires combining historical and incremental loads into a single dataset. During a JOIN, you notice duplicate rows because incremental load contains rows already present in historical. Describe SQL and ETL practices to avoid duplicate counting: merge strategies, dedupe keys, using EXCEPT or NOT EXISTS in incremental load, and verification queries.

EasyTechnical

41 practiced

You see a query using LEFT JOIN that returns fewer rows than the left table. Describe diagnostic SQL steps to find the cause: check join cardinality, nulls in join keys, misplaced WHERE filters, and unexpected duplicates on the right table. Provide specific queries you would run to debug.

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