Begin by identifying the specific data you need from the public API and how it should be structured in Convex. This includes understanding the data types, schema, and any relationships or constraints that must be maintained.

Obtain access to the public API by reviewing its documentation. You'll need to note the API's endpoints, authentication requirements (if any), and data format (typically JSON or XML). Make sure you have any necessary API keys or credentials.

Use a programming language like JavaScript or Python to fetch data from the API. You can use the `fetch` method in JavaScript or `requests` in Python to make HTTP requests to the API endpoints. Ensure you handle any pagination if the API returns data in pages.

Once the data is fetched, transform it into the structure expected by Convex. This may involve renaming fields, converting data types, and filtering out unnecessary information. Use functions or scripts to automate this process and ensure data consistency.

On the Convex platform, define the schema that will hold your data. This involves creating tables and specifying the fields, data types, and any relationships or constraints. This step ensures Convex is ready to store the incoming data.

Write a script or program to insert the transformed data into Convex using its API or SDK. This typically involves making HTTP POST requests with the data payload to Convex's data endpoints. Use loops or batch processing to handle large datasets efficiently.

After the data is uploaded, perform checks to ensure it has been transferred accurately and completely. This can include comparing sample records between the API and Convex, and setting up monitoring to alert you to any future discrepancies or issues with the data transfer process.

By following these steps, you can effectively move data from a public API to Convex without relying on third-party connectors or integrations.