Totals can be wrong when a base row joins to many detail rows.
Section: Common pitfalls
One-to-many joins can duplicate facts
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Joining customers → orders → line_items can multiply rows fast.
Aggregate carefully, often at the lowest needed grain first.Explanation
This is one of the most common analytics bugs in SQL.
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Same sheet · prioritizing Common pitfalls
Missing or incomplete ON clause
A bad join predicate can explode row counts.
WHERE on the right side can break a LEFT JOIN
Filtering after the join can remove rows you meant to preserve.
Mismatched data types hurt join quality
Joining `INT` to `TEXT` or differently formatted keys can block index use and create hidden bugs.