Begin by accessing your SAP Fieldglass account. Navigate to the report or dataset you wish to export. Utilize the built-in export functionality to download the data in a supported format, such as CSV or Excel. Ensure the export captures all necessary data fields required for your analysis.

Once you have the exported data file, open it using a spreadsheet application or a text editor. Verify the data integrity and structure. Clean and format the data as needed, removing any unnecessary columns or rows, and ensure that the data types align with what you will use in Snowflake.

Log into your Snowflake account and create a stage to temporarily store the data file. This can be done with the SQL command:
```sql
CREATE STAGE my_stage;
```
This stage acts as a storage location in Snowflake where files can be uploaded before loading them into tables.

Use the Snowflake web interface or command line tools to upload your data file to the created stage. You can use the following command to upload your file:
```sql
PUT file://path_to_your_local_file.csv @my_stage;
```
Replace `path_to_your_local_file.csv` with the actual file path on your local machine.

Before loading the data, create a table in Snowflake that matches the structure of your data file. Define the table schema using the `CREATE TABLE` command, ensuring that column names and data types match your prepared file:
```sql
CREATE TABLE my_table (
column1 STRING,
column2 INTEGER,
column3 DATE
-- Add additional columns as needed
);
```

Use the `COPY INTO` command to load data from the stage into the created table in Snowflake. This command reads from the staged file and inserts the data into the table:
```sql
COPY INTO my_table
FROM @my_stage/file_name.csv
FILE_FORMAT = (TYPE = 'CSV', FIELD_OPTIONALLY_ENCLOSED_BY = '"');
```
Ensure the `file_name.csv` matches the uploaded file, and adjust the `FILE_FORMAT` options as necessary based on your file’s characteristics.

After loading the data, execute SQL queries to verify that the data in Snowflake matches the original data from SAP Fieldglass. Check for any discrepancies in data types, missing values, or inaccuracies. Perform sample queries to ensure data is queryable and consistent with your expectations.

By carefully following these steps, you can manually transfer data from SAP Fieldglass to Snowflake without relying on third-party integrations, ensuring a custom and controlled data migration process.