How many times have we heard Garbage In, Garbage Out? How many times have we sought to answer questions about our business, only to find that one of the following applies: the data we need doesn’t exist, we have it but don’t know where it is, there are gaps in the data, there are conflicting data sources? How do you change a culture of data ‘belonging’ to the systems that generated them when all data should belong to the enterprise? I’ve spent my entire career building up Social Security’s Data Governance program: establishing naming and modeling standards, evolving our master reference data management, and more recently adapting our standards to NoSQL. We’ve always been behind the curve trying to catch up with run-away technologies that evolve the data landscape. With our Kafka onboarding, Data Governance starts with our first Production Deployment with schema registries, topic and subject naming standards and Enterprise Data Architect oversight. Learn how our approach of Data Governance as a Service to our customers will help us get ahead of the curve to helps streamline Kafka adoption for new use cases and build a reliable Enterprise Data Mesh as we go.