The QA Pitfall That Tricks Most Data Engineers

Why matching row counts are the “silent killer” of data integrity.

Zach Quinn

— 5 min read
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For years, the opening of The Simpsons (Bart writing on the chalkboard) has been very relatable. Not because I’m up to mischief.

Or at least none I’ll admit to in this forum.

But because, most days, I find myself writing the same query pattern over and over.

It features the aggregate COUNT() function and spans just three lines.

SELECT {date_field}, COUNT(*) 
FROM table 
GROUP BY {date_field} 
ORDER BY {date_field} DESC;

The output of this tells me exactly how my day is going to go.

If the most recent day’s data is in, then my phone doesn’t buzz with alerts, and I don’t spend a morning combing through logs to understand why something didn’t load.

If the data isn’t in or the count is less than expected, then I drop everything and make a diagnosis.

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