Data Migration Reconciliation and Cutover
Row counts matched on both sides at cutover. Month-end totals disagreed by eleven thousand. The count had been the only check anyone wrote down.
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Parallel Run
In a fictional telecom, a parallel run compared month-end figures from both systems and exposed a rounding rule the legacy report had applied for nine years.
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Migration Fallback
In a fictional telecom, a standalone backup lacked six days of changes. Returning required a tested procedure to recover state, transfer write authority, and reconnect clients.
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Case: Data Platform Migration for AI Consumers
A fictional distributor replaces its warehouse while a search index and a prediction model depend on the old outputs. Contracts, dual running, reconciliation, and a coded cutover rule decide when each consumer moves.
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Accepted Break
Not every difference found in a data migration is worth fixing. An accepted break records the ones the team will live with: who approved them, why, how far they extend, and when the approval lapses.
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Decision Flip Rate
After a data migration, many feature values differ slightly. The decision flip rate counts only the cases where a downstream decision actually changes, which is what the consumer of the data cares about.
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Dual Running
During a data platform migration, both pipelines process the same inputs and a comparison reports what differs. What makes the comparison trustworthy is the shared input, the key used to match rows, and a window long enough to see rare events.