Which is a good use-case for the SchemaScanner transformer?

Which is a good use-case for the SchemaScanner transformer?

• A. You have a dataset with a known, fixed schema, and you'd like to add a LastModified timestamp attribute.
• B. You have a dataset with an unknown and changing schema, and you'd like to write out whatever data you are given to a database every time the workspace runs.
• C. You have a dataset with an unknown and changing schema; you want to test the incoming attributes against a number of requirements before writing them to a database.
• D. You have a dataset with an unknown and changing schema; you want to write out the parts of the schema that match a predefined external schema.

Answer: (C)

SchemaScanner is most useful when you’re dealing with data whose schema is unknown or can change, and you want to verify that incoming attributes meet certain rules before storing them. It lets you inspect the attributes that arrive, apply a set of requirements (like presence of fields, data types, and value constraints), and only proceed if they pass. This validation step helps prevent schema drift from causing issues downstream when writing to a database. In other words, you’re testing the incoming attributes against a number of requirements prior to persisting them. The other scenarios describe fixed-schema operations, dumping all data, or mapping to an external schema—tasks that aren’t the primary purpose of SchemaScanner.

SchemaScanner is most useful when you’re dealing with data whose schema is unknown or can change, and you want to verify that incoming attributes meet certain rules before storing them. It lets you inspect the attributes that arrive, apply a set of requirements (like presence of fields, data types, and value constraints), and only proceed if they pass. This validation step helps prevent schema drift from causing issues downstream when writing to a database. In other words, you’re testing the incoming attributes against a number of requirements prior to persisting them. The other scenarios describe fixed-schema operations, dumping all data, or mapping to an external schema—tasks that aren’t the primary purpose of SchemaScanner.