Trustworthy Data from the Ground Up: The Crucial Foundation : If you build a matching algorithm before verifying your source data is complete and duplicate-free, every match it produces is quietly built on sand : The 10 milestones on this article show you how to make each layer trustworthy before the next layer depends on it.

Why order matters at all:
Milestones 1–8 — Getting the data foundation rock solid: Documentation as source of truth · Connecting settings to real measurement · Fair, repeated comparison · Representative sampling before full scale · Crash-testing the winner · Fingerprinting your source data · The full production run · Full reconciliation before trusting anything
Milestones 9–10 — Making the data searchable: The canonical search layer · Exact identifier matching, first
The bigger picture: from raw data to a trustworthy answer
The three different kinds of “percentage”