A
Data analysts often need to either combine related datasets or append similar datasets together. Knowing whether to use a JOIN or a UNION is a basic but important SQL decision because the result shape and meaning are very different.
Explain the difference between a JOIN and a UNION in SQL in the context of data analysis.
Your answer should address:
JOINUNION or UNION ALLThe interviewer is looking for a practical explanation, not just syntax definitions. Focus on how these operations change the structure of data, what business questions they answer, and why using the wrong one can lead to incorrect analysis.
A JOIN links rows from two tables based on a related key, such as customer_id or order_id. In analysis, this is used when different attributes are stored in separate tables and need to be brought together into one wider result.
SELECT o.order_id, c.customer_name
FROM orders o
JOIN customers c
ON o.customer_id = c.customer_id;
A UNION stacks the rows from two compatible SELECT statements into one result set. It is used when the queries return the same logical columns and you want one longer table rather than more columns.
SELECT customer_id, order_date AS activity_date
FROM orders
UNION
SELECT customer_id, signup_date AS activity_date
FROM customers;
UNION removes duplicate rows, while UNION ALL keeps all rows. In analytics, UNION ALL is often preferred unless deduplication is explicitly required, because duplicate removal can change counts and add extra processing.
SELECT region FROM current_regions
UNION ALL
SELECT region FROM archived_regions;
A JOIN usually increases the number of columns because it merges attributes from multiple sources. A UNION keeps the same number of columns and increases the number of rows by appending one dataset to another.
Using a JOIN when you meant to append datasets can multiply rows and inflate metrics. Using a UNION when you meant to enrich rows can lose relationships between entities and omit needed columns.
