What happens when breaking changes are made to a schema?

When breaking changes are made to a schema, data integrity may be compromised because these types of changes can alter the way data is organized, validated, or accessed within that schema. For instance, if a field is removed or its type is changed, existing data that relies on that schema may no longer conform to the new structure, leading to potential issues in how data is interpreted or processed. This is especially critical in environments where different systems and applications depend on consistent data formats for reliable operation. Maintaining data integrity is essential for ensuring that business processes function correctly and that analytics and reporting remain accurate.

The other choices highlight different implications of schema changes but do not accurately represent the consequences of breaking changes. Automatic updates could introduce inconsistencies and would not aid in maintaining data integrity. The deletion of datasets is a more drastic action that usually isn't a default response to schema changes. Finally, while existing data may not be altered immediately by schema updates, the potential for integrity issues remains. Thus, recognizing that breaking changes can compromise data integrity is crucial in the context of schema management.