Begin by thoroughly reviewing the Dixa API documentation. You need to understand how to authenticate, access endpoints, and retrieve the necessary data. Note the rate limits and data structure of the API responses.

Create an API key or token in your Dixa account. This will be required for making authenticated requests to the Dixa API. Ensure your API key has read permissions for the data you intend to export.

Use a scripting language like Python or a command-line tool like curl to make GET requests to the relevant Dixa API endpoints. Collect the data you need, such as customer interactions, user information, or conversation history. Save this data in a structured format, such as JSON or CSV.

Once you have the raw data, process and clean it to match your MSSQL schema. This might involve transforming JSON data into tabular form, renaming fields, or removing unnecessary information. You can use scripting languages like Python for data manipulation.

Ensure your MSSQL database is prepared to receive the data. Create tables that match the structure of your cleaned data. Define the appropriate data types, primary keys, and any necessary indexes to optimize performance.

Use SQL Server Management Studio (SSMS) or a script to insert the cleaned data into your MSSQL database. If your data is in CSV format, you can use the BULK INSERT command in T-SQL to load the data efficiently. For JSON, consider using OPENJSON in T-SQL to parse and insert the data.

After insertion, verify that all data has migrated correctly by running queries to compare the dataset in MSSQL with the original data in Dixa. Once confirmed, consider automating this process using scripts or stored procedures to handle regular data transfers.

By following these steps, you can manually transfer data from Dixa to MSSQL without relying on third-party connectors or integrations.