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Build an ML training set in SQL with point-in-time-correct feature joins (no future leakage).

The single most common way SQL leaks the future into a training set is a careless join to a feature table. Point-in-time correctness is the fix, and it is an as-of join. Here is how to write it.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

The single most common way SQL leaks the future into a training set is a careless join to a feature table. Point-in-time correctness is the fix, and it is an as-of join. Here is how to write it.

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