How to load data from Smaily to Snowflake destination

Learn how to use Airbyte to synchronize your Smaily data into Snowflake destination within minutes.

Try Airbyte Cloud Manual method (the hard way)

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Smaily connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Snowflake destination for your extracted Smaily data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Smaily to Snowflake destination in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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How to Sync to Manually

Step 1: Extract Data from Smaily

Begin by logging into your Smaily account. Navigate to the section where your data is stored (e.g., contacts, campaigns). Utilize Smaily's export functionality to output the data you need. Typically, you can export data in CSV or Excel format, which are widely supported formats for data handling.

Step 2: Prepare Data Locally

Once you've exported the data from Smaily, save it on your local machine. Open the file to ensure that the data is correctly formatted and contains all necessary fields. Perform any required data cleaning, such as removing duplicates, correcting errors, or reformatting columns to ensure compatibility with Snowflake's schema.

Step 3: Install SnowSQL Command-Line Tool

Download and install SnowSQL, Snowflake's command-line interface tool. This tool will be essential for loading data into Snowflake. Follow the installation instructions provided by Snowflake's documentation to set up and configure SnowSQL on your machine.

Step 4: Configure Snowflake Environment

Set up your Snowflake account by logging into the Snowflake web interface. Create a new database and schema where you intend to store the imported data. Define the necessary tables that match the structure of your Smaily data, including appropriate data types for each column.

Step 5: Stage Data for Upload

Before uploading, stage your data by converting it into a format suitable for bulk upload. Use the CSV format if it's not already in that format. Compress the file using gzip to optimize the transfer speed and reduce storage requirements.

Step 6: Upload Data to Snowflake Stage

Use the SnowSQL tool to upload your data file to a Snowflake stage. Execute the `PUT` command to transfer the file from your local machine to a specified stage in your Snowflake account. Ensure you have the correct permissions and that the stage path is correctly specified.

Step 7: Load Data into Snowflake Table

Finally, execute the `COPY INTO` command in SnowSQL to load the staged data into your Snowflake table. This command will move the data from the stage into the database table, completing the data transfer process. Verify the data load by querying the table and checking if the records match your source file.

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