Why is schema validation significant in data integration?

Schema validation is fundamental in data integration because it ensures that the data adheres to a defined structure. When data is exchanged between different systems, it is critical that it conforms to specific formats, types, and constraints as outlined in the schema. This structured approach guarantees that all participating systems can understand and process the data correctly.

By enforcing schema validation, organizations can maintain data integrity and prevent issues that could arise from improperly formatted data. For instance, if a system expects a date field in a specific format but receives it in another, it could lead to errors, data loss, or misinterpretation. Validating data against a defined schema before it is integrated minimizes these risks and facilitates seamless communication between disparate systems.

The other options reflect different aspects of data processing and integration but do not encapsulate the core importance of schema validation in maintaining the integrity and proper structure of data, which is the essence of successful data integration.