Begin by familiarizing yourself with the data structure and format in Railz. Identify the datasets or specific data points you need to transfer. This step is crucial to ensure you know what data you are dealing with and how it needs to be represented in MSSQL.

Use Railz's native export functionality to extract the data you need. This might involve using APIs or downloading data in formats such as CSV or JSON. Make sure to follow any Railz documentation or guidelines on how to properly export data to ensure you capture everything required.

Set up your MSSQL database and tables to receive the data. Define the schema that matches the structure of your exported data from Railz. This might involve creating tables with the correct columns and data types that correspond to your Railz data.

Before importing into MSSQL, clean and transform the exported data to align with the MSSQL schema. This might involve data cleaning tasks such as removing duplicates or correcting data types, and transforming tasks like converting date formats or restructuring JSON data into tabular format.

Use MSSQL's built-in tools such as the SQL Server Management Studio (SSMS) or command line utilities like `bcp` or `SQLCMD` to load your cleaned and transformed data into the database. These tools allow you to import data in formats like CSV directly into MSSQL.

Once the data is imported, verify its integrity and completeness. Run queries to ensure all data has been transferred correctly and check for any discrepancies between the source data in Railz and the target data in MSSQL.

If you need to perform this data transfer regularly, consider scripting the entire process using batch scripts or stored procedures in SQL Server. This will automate the data extraction, transformation, and loading process, saving time and reducing the potential for human error in future transfers.

By following these steps, you can transfer data from Railz to an MSSQL destination efficiently without relying on third-party connectors or integrations.