What function does Delta's change data capture (CDC) serve in Databricks?

Delta's change data capture (CDC) functionality is designed to allow real-time tracking of data changes within a dataset. This capability is crucial for keeping data in sync across various systems and for applications that require timely updates based on changes in the underlying data. By leveraging CDC, organizations can efficiently handle insertions, updates, and deletions that occur in their data tables, ensuring that downstream applications and data consumers have access to the most current information.

Real-time tracking through CDC is especially beneficial for use cases involving streaming analytics, real-time dashboards, or event-driven architectures, where it is critical to respond promptly to changes in the data. This mechanism helps maintain data integrity and accuracy by capturing every change as it happens, thereby supporting a more dynamic and responsive data ecosystem.

In contrast, while options related to batch processing, data warehousing management, and schema evolution are important aspects of data management, they do not specifically address the immediate tracking of changes within datasets in the same real-time context that Delta's CDC offers.