1. Ensure Connectivity: Make sure you can connect to your Redshift cluster from the machine where you'll perform the data transfer.

2. Verify Permissions: Ensure you have the necessary permissions to read the data from Redshift and to write data to SQL Server.

3. Identify Data: Determine which tables and data you want to move to SQL Server.

1. Choose a Format: Decide on a file format for the exported data (e.g., CSV).

2. Connect to Redshift:

   - Use a SQL client or command-line tool to connect to your Redshift cluster.

   - Example using `psql`:

     ```

     psql -h redshift-cluster-identifier -U your-username -d your-database -p 5439

     ```

3. Export Data:

   - Execute a `UNLOAD` command to export the data to Amazon S3.

   - Example:

     ```sql

     UNLOAD ('SELECT * FROM your_table')

     TO 's3://your-bucket/your-data-prefix'

     CREDENTIALS 'aws_access_key_id=your_access_key_id;aws_secret_access_key=your_secret_access_key'

     DELIMITER ','

     ADDQUOTES

     ESCAPE

     ALLOWOVERWRITE

     PARALLEL OFF;

     ```

4. Download the Files:

   - Use the AWS CLI or S3 interface to download the exported files to your local machine or directly to the machine with SQL Server access.

   - Example using AWS CLI:

     ```

     aws s3 cp s3://your-bucket/your-data-prefix ./data --recursive

     ```

1. Create Tables: Define the schema in SQL Server to match the Redshift tables you are importing.

2. Set Up Database Access: Ensure that the SQL Server instance is accessible and that you have the necessary permissions to write data.

1. Connect to SQL Server:

   - Use SQL Server Management Studio (SSMS) or another SQL client to connect to your SQL Server instance.

2. Format Files: Make sure the flat files conform to SQL Server's bulk insert requirements (e.g., correct delimiters, text qualifiers, etc.).

3. Import Data:

   - Use the `BULK INSERT` command or SQL Server Import and Export Wizard to load the data from the flat files into the SQL Server tables.

   - Example `BULK INSERT` command:

     ```sql

     BULK INSERT your_table

     FROM 'C:\data\your-file.csv'

     WITH (

       FIELDTERMINATOR = ',',

       ROWTERMINATOR = '\n',

       FIRSTROW = 2,

       QUOTECHARACTER = '"'

     );

     ```

1. Check Row Counts: Compare the row counts in SQL Server with those in Redshift to ensure all data was transferred.

2. Perform Data Validation: Run some queries to validate that the data in SQL Server matches the data in Redshift.

1. Remove Temporary Files: Delete the flat files from your local machine and any temporary storage to maintain security and free up space.

2. Close Connections: Ensure that all database connections are closed properly.

Tips and Considerations:

- Data Types: Pay special attention to data types during the import process, as some data types may not map directly between Redshift and SQL Server.

- Character Encoding: Ensure that the character encoding is consistent between the exported data and the SQL Server import process.

- Security: When dealing with sensitive data, make sure to follow best practices for data security, including using secure connections and handling credentials securely.

- Backup: Always have a backup of your data before performing such operations.

- Transaction Logs: For large data imports, be mindful of the transaction log size in SQL Server. It may be necessary to perform the import in batches or to adjust the recovery model temporarily.

By following these steps, you should be able to move data from Amazon Redshift to Microsoft SQL Server without using third-party connectors or integrations. Remember that this process can be time-consuming and may require trial and error to handle the nuances of data types and file formatting.