How to load data from SFTP to Snowflake destination

1. Log in to the SFTP server: Use an SFTP client or command-line tool to connect to the SFTP server with the appropriate credentials.

2. Locate the data files: Navigate to the directory where the data files you want to move are stored.

3. Export the data (if necessary): If the data isn't already in a flat-file format (CSV, JSON, etc.), export it to a format that Snowflake can ingest.

4. Compress the data (optional): To speed up the transfer, you can compress the data files using a tool like `gzip`.

Snowflake can directly load data from cloud storage services like Amazon S3, Google Cloud Storage, or Azure Blob Storage. Choose the one that is most suitable for your Snowflake account and region.

If using Amazon S3:

1. Install AWS CLI: Install and configure the AWS Command Line Interface (CLI) with the necessary permissions to access your S3 bucket.

2. Upload to S3: Use the AWS CLI to upload the data files from your local machine to the appropriate S3 bucket using the `aws s3 cp` or `aws s3 sync` command.

If using Google Cloud Storage:

1. Install Google Cloud SDK: Install and configure the Google Cloud SDK with the necessary permissions to access your Cloud Storage bucket.

2. Upload to GCS: Use the `gsutil cp` command to upload the data files from your local machine to the appropriate Cloud Storage bucket.

If using Azure Blob Storage:

1. Install Azure CLI: Install and configure the Azure Command Line Interface (CLI) with the necessary permissions to access your Blob Storage container.

2. Upload to Blob Storage: Use the `az storage blob upload` command to upload the data files from your local machine to the appropriate Blob Storage container.

Once the data is in cloud storage, you can load it into Snowflake using the COPY INTO command.

1. Log in to Snowflake: Use the Snowflake web interface or a SQL client that supports Snowflake to log in to your account.

2. Create a File Format: Define a file format that matches the format of your data files:

```sql

CREATE FILE FORMAT my_file_format

TYPE = 'CSV'

FIELD_DELIMITER = ','

SKIP_HEADER = 1

NULL_IF = ('\\N');

```

3. Create a Stage: Create a stage object that points to the location of the files in the cloud storage:

```sql

-- For Amazon S3

CREATE STAGE my_stage

URL = 's3://mybucket/data/'

FILE_FORMAT = my_file_format

CREDENTIALS = (AWS_KEY_ID = 'my_aws_key_id' AWS_SECRET_KEY = 'my_aws_secret');

-- For Google Cloud Storage

CREATE STAGE my_stage

URL = 'gcs://mybucket/data/'

FILE_FORMAT = my_file_format

CREDENTIALS = (GCS_CREDENTIALS = 'my_gcs_credentials_json');

-- For Azure Blob Storage

CREATE STAGE my_stage

URL = 'azure://myaccount.blob.core.windows.net/mycontainer/data/'

FILE_FORMAT = my_file_format

CREDENTIALS = (AZURE_SAS_TOKEN = 'my_azure_sas_token');

```

4. Create a Target Table: Create a table in Snowflake to hold the data:

```sql

CREATE TABLE my_table (

column1 STRING,

column2 STRING,

...

);

```

5. Copy Data into Snowflake: Use the COPY INTO command to load the data from the stage into the Snowflake table:

```sql

COPY INTO my_table

FROM @my_stage

FILE_FORMAT = (FORMAT_NAME = my_file_format);

```

6. Verify the Data Load: After the COPY INTO command completes, verify that the data has been loaded correctly:

```sql

SELECT * FROM my_table LIMIT 10;

```

After the data has been successfully loaded into Snowflake, you may want to clean up any temporary files or data that is no longer needed.

1. Remove Temporary Files: If you created any temporary files during the process, make sure to delete them from your local machine and cloud storage.

2. Close SFTP Connection: Log out from the SFTP server to ensure security.

3. Review Snowflake Costs: Loading data into Snowflake may incur costs, so review your usage and consider setting up resource monitors to manage expenses.

Remember to handle any sensitive credentials securely and to rotate them periodically. Also, consider automating this process for recurring data transfers using scripting and scheduling tools.