Most of the value in Data Migrations appears before anyone says done. The useful work is usually in the questions, the examples, and the evidence that changes the conversation.
My checklist for Data Migrations is not meant to turn testing into box-ticking. It exists so pressure does not erase the few important questions that protect integrity, backfills, reversibility, and watching data change safely. The risk never stays theoretical for long, because the schema update succeeds while the meaning of old records quietly shifts underneath it.
A good checklist keeps important risk visible when the room gets busy.
Before I Start
- Make the change area explicit
- Write down the most expensive failure in one sentence
- Confirm which database owners and teams carrying historical data forward should review open risk
- Choose the environment that will tell the truth fastest
During the Check
- Exercise the normal path that should protect integrity, backfills, reversibility, and watching data change safely
- Run an awkward-path example based on a migration finishes on time but leaves a small slice of historical data partially transformed
- Watch for mismatches between visible success and hidden state
- Capture the one detail that will matter during sign-off later
Before I Close the Work
I finish by asking whether the evidence would still make sense to someone who was not present during testing. For this topic, the evidence I want usually looks like sampled before-and-after records, fallback steps, and checks for partial completion.
If the answer is yes, the checklist did its job. If the answer is no, I am not done yet. I keep the practice alive because it improves both release quality and team clarity at the same time.