Stop Reacting to Data Problems. Here’s the Architecture That Prevents Them
Brief
Coauthored by Satyajeet
Coordinating Data Evolution at Enterprise Scale
When you operate data platforms on a global enterprise scale, hundreds of engineering teams ship improvements every week, each moving independently to deliver value at the pace of the business demands. This velocity is a competitive advantage. The challenge: How do you enable hundreds of teams to evolve their data products independently while maintaining reliability for thousands of downstream consumers?
Traditional coordination methods (messages, wiki updates, shared spreadsheets) work at small scale but break at Walmart scale. A source team ships an enhancement, perfectly valid within their domain, but that change ripples through fifteen downstream pipelines owned by different teams with different release schedules. Without a formal coordination mechanism, you discover the impact after it reaches production.