This workflow automates the process of synchronizing product insights, features, and companies from Productboard into Snowflake, a cloud-based data warehouse, and sending weekly Slack updates. It is designed to keep product teams informed with up-to-date data and insights without manual effort.
The workflow begins with a scheduled trigger that runs weekly, setting the process in motion. It first prepares the Snowflake database by truncating existing tables for features, notes, companies, and their interrelations, ensuring clean data import. It then fetches companies, notes, and features from the Productboard API, handling pagination to retrieve complete datasets.
Each data set (companies, notes, features) is processed with nodes that map API response data into a structured format suitable for database insertion. The workflow also manages relationships between notes and features by matching IDs. The data is then inserted into the appropriate Snowflake tables.
Additionally, the workflow calculates the number of new insights added in the last 7 days and the number of unprocessed insights, sending a summarized update as a Slack message with an overview and a link to a dashboard.
This automation is ideal for product managers and teams who want real-time, automated updates of their product data, reducing manual data entry and ensuring everyone stays informed with the latest insights and status changes.
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