Data architecture and management strategies
Eventual consistency in DDD works when the inconsistency window is a business number. Build a .NET saga with outbox and idempotent consumers, then alert on it.
Event Sourcing stores every state change as an immutable event, so your database keeps the full history. When to use it, and a working C# implementation.
It started with one of the tasks on our project kanban board: "Data migration". We were building a new application for a telecom provider. The goal was to unify two old systems into a single custom-built platform. Development was already in motion. Sprints were delivering new features. But no one had touched the data. The legacy systems had mismatched schemas, overlapping records, and different definitions for the same business terms. Some orders were in one system, but not the other. Customer records had conflicting states. Worse, every new feature we built had to be fed by clean, compatible data. Any mismatch would break logic or trigger errors in production.