Integrating data streams with legacy systems: Map out all data touchpoints & formats Use middleware as a bridge between old & new Transform data to ensure compatibility Set up clear error monitoring Test thoroughly before full deployment Document every integration step Have rollback plans ready

The first step should always be taking a step back and understanding what data from the legacy systems actually need to be integrated. Integrating new and legacy data systems can a great opportunity to address tech debt and strengthen data architecture. Some good questions to ask: -What data are needed for all end deliverables? -Are there any end deliverables that are obsolete but still being maintained? -How much of the required data are available or can be easily reproduced in the new data system(s)? Don't just turn off legacy systems, though; integrating these systems should be an incremental process. But without a higher-level assessment, you may spend lots of time integrating legacy data that don't need to be integrated.

Think of legacy systems as vintage houses - you wouldn't tear down load-bearing walls without proper planning! Beyond middleware, success lies in establishing an Integration Competency Center (ICC) that governs your integration patterns. Consider TOGAF's Technical Reference Model for mapping interfaces, then implement an ESB or API gateway with proper data mapping schemas. The key? Start small with a pilot integration, validate patterns, then scale. Remember: architecture is about evolution, not revolution.