Sample Answer
On a data migration project for about 1.5M customer records, I was worried about two things from day one: data quality issues from legacy systems and potential downtime during cutover. In the risk log, I quantified both: we estimated up to 8–10% of records might be incomplete, and even a one-hour outage could impact roughly $150k in transactions. We built in three mitigations: a pre-migration data profiling pass, a staged migration with 10%/30%/60% cohorts, and a rollback plan with read-only mode. During the first 10% cohort, we actually hit 9% bad records, mostly due to legacy formatting. Because we’d planned for it, we paused, ran automated cleanup scripts we’d already prepared, and re-ran that batch overnight with zero customer-visible impact. By the time we did the full cutover, error rates were under 1% and we stayed within a 10-minute read-only window instead of a full outage.
Keywords
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