Begin by setting up a connection to your Teradata database. Install the necessary Teradata client tools such as Teradata CLI or ODBC drivers on your local machine. Use these tools to authenticate and establish a session with the Teradata database. Make sure you have the necessary credentials and network access to connect to the database.

Once connected, write an SQL query to extract the data you need from Teradata. Use SQL commands to select the specific tables or fields you want to export. Make sure your query is efficient to minimize load on the database server.

Use Teradata's export utilities like BTEQ (Basic Teradata Query) to execute your query and save the output to a local file in a delimited format, such as CSV. Execute the BTEQ script containing your SQL query and redirect the output to a local file on your machine.

Ensure that you have a JSON processing tool or library available on your local machine. If you are using a programming language like Python, you can use its built-in `json` module. For other languages, ensure you have equivalent JSON parsing and generation capabilities.

Write a script to read the exported file. If your data is in CSV format, you can use CSV reading utilities (such as Python's `csv` module) to parse the data line by line. Make sure to handle any special characters or delimiters properly.

Transform the parsed data into JSON format. Create a list or array of dictionaries (or equivalent data structures in your programming language) that mirrors the structure of your exported data. Use your JSON processing tool to serialize this data structure to JSON.

Finally, write the JSON data to a local file. Use file handling functions to create a new file and write the JSON data into it. Make sure to handle file opening, writing, and closing operations carefully to prevent data loss. Name the file appropriately and verify that the data has been written correctly by opening and inspecting the JSON file.