You're facing unexpected schema changes. How can you ensure downstream data consumers are unaffected?

1- Prefer First to Use schema versioning to track and manage changes. 2- Ensure backward compatibility to avoid breaking existing functionality. 3- Update data pipelines to handle the new schema. 4- Inform stakeholders about the changes.

Versionamento de Esquema: Mantenha múltiplas versões do esquema. Ao realizar alterações, introduza uma nova versão do esquema em vez de modificar o existente. Isso permite que os consumidores continuem usando a versão antiga até que estejam prontos para migrar para a nova. Contratos de Dados: Estabeleça contratos de dados claros entre os produtores e consumidores. Esses contratos definem quais partes do esquema são garantidas e não devem mudar sem aviso prévio. Compatibilidade Retroativa: Assegure que as mudanças no esquema sejam retrocompatíveis. Por exemplo, ao adicionar novos campos, faça isso de maneira que as aplicações existentes, que não conhecem os novos campos, ainda possam funcionar corretamente.

-Schema Registry: Use a schema registry (e.g., Confluent) to manage and enforce backward/forward compatibility. -Blue-Green Deployment: Implement blue-green deployments for schema changes, allowing for testing in a production-like environment before full rollout. -Feature Toggles: Use feature toggles to switch between old and new schemas without disrupting consumers. -CI/CD Pipelines: Integrate automated schema validation in CI/CD pipelines to catch issues early. -Real-Time Data Validation: Use real-time data validation tools (e.g., Datafold) to monitor and compare schema changes in production.

Form a change committee with representatives of downstream consumers. Document upcoming changes often and early. Plan releases accordingly, work with clients to coordinate. Inform your data consumers early that change is coming. Implement design patterns that help with downstream system robustness - add columns, but don't drop columns. Document and publish changes to downstream consumers. If a change is especially disruptive, consider creating new schema objects, and again fully document and publish the changes to downstream consumers. Educate data consumers to build specificity into their solutions - in effect ban the use of SELECT * Playing loose and fast will introduce fragility in the consumer systems, specificity equates to robust code