Part 8/13:
While data quality is often verified during development and testing, maintaining this in production remains a challenge. The session emphasized the importance of embedding data quality checks within production pipelines, such as parallel validation and fail-safe mechanisms like Change Data Capture (CDC). These measures enable quick identification and rectification of issues, minimizing impact on business operations.
Understanding upstream systems is critical; data engineers are encouraged to assess whether upstream systems are capable of providing real-time data that meets organizational needs. Collaborative efforts between teams can facilitate addressing issues at source, preventing recurrent problems, and ensuring data reliability.