What are two critical components needed for a successful data pipeline in Foundry?

The choice that includes data integrity checks and monitoring setup highlights essential components necessary for a successful data pipeline in Foundry.

Data integrity checks ensure that the data entering and flowing through the pipeline is accurate, consistent, and reliable. This process helps in identifying and correcting any inconsistencies or errors within the data, ensuring that downstream processes are working with high-quality data. Monitoring setup complements this by allowing data engineers to observe the performance and health of the data pipeline continuously. By implementing a monitoring system, teams can proactively detect any issues that may arise—such as performance bottlenecks or data loss—and address them before they lead to significant problems.

Together, these components create a robust framework that not only enhances the reliability of the data pipeline but also builds trust in the data being processed. This dual focus on maintaining data integrity and establishing thorough monitoring ensures that the pipeline operates smoothly and effectively over time.