1. Create the Report or Look: Define the data you want to export from Looker by creating a report (Look) or using an existing one.
2. Run the Query: Execute the query to ensure it returns the expected data.
3. Export Data: Once the data is ready, export it from Looker in a suitable format, typically CSV or Excel, which can be later imported into Snowflake.

1. Log in to Snowflake: Access your Snowflake account.
2. Create a Database and Schema: If not already present, create a new database and schema where you want to store the Looker data.
   ‍CREATE DATABASE my_database;
USE DATABASE my_database;
CREATE SCHEMA my_schema;

3. Create a Table: Define a table in Snowflake with the appropriate schema to hold the data you’re exporting from Looker.
   ‍CREATE TABLE my_schema.my_table (
   column1 TYPE,
   column2 TYPE,
   ...
);‍

Replace TYPE with the corresponding data types for your columns.

1. Format the Data: Ensure the exported data file is in a format compatible with Snowflake’s data loading methods (CSV is commonly used).
2. Clean the Data: Make sure the data is clean, with no formatting issues that could cause errors during the import process.

1. Choose a Staging Area: Decide whether to use Snowflake’s internal staging area or an external cloud storage service (like Amazon S3, Google Cloud Storage, or Azure Blob Storage) to temporarily store the data file.
2. Upload the File: Use the PUT command for Snowflake’s internal staging or the appropriate method for your chosen cloud storage service to upload the data file.
3. For Snowflake’s internal staging:

PUT file://path_to_your_file.csv @~;

1. Copy Command: Use the COPY INTO command to load the data from the staging file into the target table in Snowflake.
   ‍COPY INTO my_schema.my_table
FROM @my_stage/path_to_your_file.csv
FILE_FORMAT = (TYPE = 'CSV' FIELD_OPTIONALLY_ENCLOSED_BY = '"' SKIP_HEADER = 1);

2. Validate Data Load: Check the loaded data to ensure it matches the exported data from Looker.
   ‍SELECT * FROM my_schema.my_table;

1. Remove Temporary Files: If you used Snowflake’s internal staging, remove the temporary files.
   ‍REMOVE @~ 'path_to_your_file.csv';

2. Review and Optimize: Evaluate the data transfer process for any optimizations for future transfers, such as automating the process with Snowflake’s tasks or stored procedures if this is a recurring need.

1. Manage Access: Grant appropriate permissions to users or roles that need access to the new data in Snowflake.
   ‍GRANT SELECT ON my_schema.my_table TO ROLE my_role;

2. Audit: Ensure that the data transfer complies with your organization’s data governance and security policies.

Important Notes:

• The data types in the Snowflake table should match the data types of the Looker exported data to prevent data conversion errors.
• Ensure that you have the necessary permissions in both Looker and Snowflake to perform these operations.
• Always validate the data after each step to ensure the integrity of the transfer.