Snowflake Data Management Workflow

This workflow is ideal for data analysts, data engineers, and developers who work with Snowflake and need to automate the process of creating tables and managing data. It is particularly useful for those who prefer manual triggers for testing or ad-hoc data operations.

This workflow addresses the need for automating the creation of tables and the insertion and updating of data in Snowflake. It simplifies the process of managing data by providing a structured approach to execute SQL commands, thereby saving time and reducing errors in manual data handling.

1. Trigger the Workflow: The workflow starts when the user clicks 'execute', initiating the process.
2. Set Initial Values: A 'Set' node is used to define initial values for the table, including an ID of 1 and a name of 'n8n'.
3. Create Table: The workflow executes a Snowflake query to create a table named 'docs' with columns 'id' and 'name'.
4. Insert Data: The workflow uses another Snowflake node to insert the initial values defined earlier into the 'docs' table.
5. Set Update Values: A second 'Set' node is employed to prepare new values for updating the table, changing the name to 'nodemation' while keeping the ID the same.
6. Update Data: Finally, the workflow updates the 'name' column in the 'docs' table using the new values set in the previous step.