Which statement best describes a typical use of SchemaScanner when dealing with schema drift?

Which statement best describes a typical use of SchemaScanner when dealing with schema drift?

• A. You can use it to compare schemas, and then use other transformers to generate a report that highlights the differences in the schema, which can be used to update the schema or modify the data accordingly.
• B. You can use it to build workspaces that will not allow schema drift to occur in the first place.
• C. You can use it to invalidate data submissions and alert end-users that they are causing schema drift.
• D. You can use it to compare schemas, and then use other transformers to create a detailed visualization of the schema changes that can be used to troubleshoot errors.

Answer: (A)

Schema drift shows up as differences between what a schema is supposed to be and what it currently is. SchemaScanner addresses this by comparing the active schema in your workspace with a reference or target schema and surfacing where names, types, or structures differ. The typical workflow is to run that comparison and then pass the results into a reporting or remediation step that highlights the differences. Those results can guide you to update the reference schema or adjust the data accordingly (for example, adapt field types, rename fields, or re-structure data) so subsequent processing stays in sync. It’s not about preventing drift upfront, invalidating submissions, or creating purely visualizations—the strength of SchemaScanner lies in producing a clear diff you can act on.

Schema drift shows up as differences between what a schema is supposed to be and what it currently is. SchemaScanner addresses this by comparing the active schema in your workspace with a reference or target schema and surfacing where names, types, or structures differ. The typical workflow is to run that comparison and then pass the results into a reporting or remediation step that highlights the differences. Those results can guide you to update the reference schema or adjust the data accordingly (for example, adapt field types, rename fields, or re-structure data) so subsequent processing stays in sync. It’s not about preventing drift upfront, invalidating submissions, or creating purely visualizations—the strength of SchemaScanner lies in producing a clear diff you can act on.