ETL & Data Pipelines Templates

This workflow retrieves customer data from a mock "Customer Datastore", then extracts and transforms specific fields (id, name, and notes) into a more structured format using the "Edit Fields" node, renaming them to customer_id, customer_name, and customer_description. This prepared data is then likely intended for use in subsequent nodes or services, although the workflow is incomplete.

This workflow allows you to send position updates of the ISS every minute to a table in Google BigQuery.  **Cron node:** The Cron node will trigger the workflow every minute. **HTTP Request node:** This node will make a GET request to the API `https://api.wheretheiss.at/v1/satellites/25544/positions` to fetch the position of the ISS. This information gets passed on to the next node in the workflow. **Set node:** We will use the Set node to ensure that only the data that we set in this node gets passed on to the next nodes in the workflow. **Google BigQuery:** This node will send the data from the previous node to the `position` table in Google BigQuery. If you have created a table with a different name, use that table instead.

This workflow automates the process of extracting data from a PDF file uploaded to Google Drive, converting it to JSON format using an AI agent, and then inserting the extracted data into a SQL Server database and a Supabase vector store. The workflow also uses embeddings and text splitting to prepare the data for the AI agent.