Document databases offer schema flexibility, which can be advantageous but sometimes requires validation to ensure data integrity, particularly in applications relying on specific document fields. The article explores how to validate JSON documents using the Python library pydantic, emphasizing the necessity of schema validation in NoSQL databases, where data structure is often perceived as unnecessary. It demonstrates setting up a JSON schema for user profiles, identifying mandatory and optional fields, and employing the open-source Faker library to generate testing data. Using pydantic, developers define a model with expected data types and validate fields, such as phone numbers, to prevent data inconsistencies. The article includes an example of schema validation by loading data into Couchbase Capella and checking for errors using pydantic's parse_obj method. The conclusion highlights the utility of pydantic for JSON document validation and suggests further integration of schema verification during data operations, with additional resources and code available on GitHub.