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Import Productboard Notes, Companies, and Features into Snowflake

This workflow automatically retrieves product notes, company information, and feature characteristics from the Productboard platform and structurally imports the data into the Snowflake data warehouse. By regularly cleaning and updating the data, it ensures the integrity and timeliness of the information. Additionally, the workflow supports data monitoring, generates weekly update statistics, and sends notifications via Slack, allowing the team to stay informed about the latest product insights, enhance decision-making efficiency, and reduce errors and complexities associated with manual operations.

Workflow Diagram
Import Productboard Notes, Companies, and Features into Snowflake Workflow diagram

Workflow Name

Import Productboard Notes, Companies, and Features into Snowflake

Key Features and Highlights

This workflow automates the extraction of product-related Notes, Companies, and Features from the Productboard platform and imports the structured data into the Snowflake data warehouse. It supports batch retrieval of paginated data, automatically cleans and rebuilds target database tables to ensure data integrity and timeliness. Weekly data update statistics are generated and pushed via Slack notifications, enabling the team to stay informed with the latest product insights in a timely manner.

Core Problems Addressed

  • Automatically synchronize dispersed product information from Productboard, eliminating the complexity and errors of manual export-import processes.
  • Unify and structure product notes, company, and feature data for easier subsequent data analysis and reporting.
  • Monitor newly added and unresolved insight notes in real time, improving product management and decision-making efficiency.
  • Integrate Slack notifications to ensure team members are promptly informed of product data updates.

Use Cases

  • Product management teams needing to regularly sync product feedback, feature planning, and customer information from Productboard into the enterprise data warehouse.
  • Data analysts performing cross-system data integration and in-depth analysis based on product data stored in Snowflake.
  • Organizations requiring automated monitoring of product insight updates and unresolved statuses to enhance response speed.
  • Teams wishing to receive real-time product data update alerts through Slack channels.

Main Workflow Steps

  1. Scheduled Trigger: Initiate the workflow at a specified weekly time via a schedule trigger.
  2. Data Cleanup: Clear the PRODUCTBOARD_NOTES, PRODUCTBOARD_COMPANIES, PRODUCTBOARD_FEATURES, and related tables in Snowflake to ensure fresh data loading.
  3. Data Extraction: Call the Productboard API to paginate through and retrieve all companies, notes, and feature data.
  4. Data Splitting and Mapping: Process the retrieved data by splitting and mapping fields to standardize the data format.
  5. Data Loading: Batch insert the mapped data into the corresponding Snowflake tables.
  6. Statistical Analysis: Calculate the number of new notes added and unresolved notes in the past 7 days within Snowflake.
  7. Slack Notification: Push the statistical results along with a Metabase dashboard link to a designated Slack channel.

Involved Systems or Services

  • Productboard API: Source for company, notes, and feature data extraction.
  • Snowflake: Data warehouse for storage and querying.
  • Slack: Channel for weekly reports and update notifications.
  • Metabase (linked): External integration for data visualization dashboards.

Target Users and Value

  • Product managers and product operations teams: Automatically obtain comprehensive and up-to-date product insight data to support product decision-making.
  • Data engineers and analysts: Simplify data synchronization workflows while ensuring data consistency and availability.
  • Enterprise executives and related business units: Gain instant visibility into product data dynamics via Slack, enhancing cross-department collaboration.
  • Any organization relying on Productboard for product management and Snowflake as their data warehouse.

This workflow significantly reduces manual effort in product data synchronization and monitoring, enhances automation and efficiency in data processing, and serves as an effective bridge between product management and data analytics.