When data sources change unexpectedly during integration, adaptability is key. First, I quickly assess the changes—whether they involve schema, format, or structure. Then, I leverage dynamic data pipelines and schema evolution techniques to adjust mappings without disrupting workflows. Using a robust data integration platform, I implement validation checks to handle anomalies and ensure data integrity. Proactive monitoring and communication with stakeholders keep the process seamless while minimizing downtime

O processo de integração de dados exige atenção e planejamento. É preciso mapear as fontes de dados, desenhando a arquitetura e os pontos de integração. Mas, mesmo assim imprevistos podem acontecer e, nestes casos, o primeiro passo é entender o que aconteceu e porque das mudanças, para então remapear a arquitetura de dados e refazer as integrações. Além disso, é importante ter um ambiente de teste e outro com backup, para viabilizar o controle de qualidade e dar redundância.

Quickly assess the new structure and identifying differences. Update your ETL (Extract, Transform, Load) processes to handle the changes, including any new formats or fields. Use data validation tools to check for errors or inconsistencies. Communicate the changes clearly to all stakeholders to align expectations. Perform incremental testing on the updated integration pipeline to ensure seamless processing before deploying the full system. This flexible approach helps maintain reliability and minimizes disruptions.