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.

MediumTechnical

0 practiced

Write SQL to perform a left join but include a column that indicates whether the right-side match was unique, multiple, or missing (e.g., match_status: 'no_match', 'single_match', 'multiple_matches'). Use aggregation or window functions to compute match_status per left row.

MediumTechnical

0 practiced

You need to avoid double-counting when joining customers to orders and order_items. Schemas:

sql

customers(customer_id)
orders(order_id, customer_id)
order_items(item_id, order_id, product_id, quantity, price)

Write a query that reports total revenue per customer without double-counting when an order appears multiple times (e.g., deduped orders). Explain strategies to prevent multiplicative joins causing over-counting.

EasyTechnical

0 practiced

Using a transactions table:

transactions(tx_id INT, customer_id INT, tx_date DATE, amount NUMERIC)

, write two SQL approaches (one using LEFT JOIN ... IS NULL and one using NOT EXISTS) to find customers in customers(customer_id) who had no transactions in the past 365 days. Which approach is typically more efficient and why?

EasyTechnical

0 practiced

You need to join customer and survey responses but only want the latest response per customer for each survey type, then compute NPS. Schema:

sql

customers(customer_id)
surveys(survey_id, customer_id, survey_type, submitted_at, score)

Write SQL to select latest survey per customer and survey_type and compute average score by survey_type.

EasyTechnical

0 practiced

You have two tables in a PostgreSQL data warehouse:

sql

customers(customer_id INT PRIMARY KEY, name TEXT, state TEXT, signup_date DATE)
orders(order_id INT PRIMARY KEY, customer_id INT, order_date DATE, amount NUMERIC)

Write a SQL query that returns customer_id, name, total_orders, total_amount for customers in state = 'CA' who placed at least one order in the last 30 days. Use a single JOIN with multiple join/filter conditions so the join only considers orders in the 30-day window and customers from CA. Explain why you placed filters in ON vs WHERE.

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