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The HR Roster Change Detection Pipeline is an automated solution for processing HR roster data. Leveraging Apache Airflow and PostgreSQL, it enables seamless data ingestion, deduplication, and change detection, streamlining HR operations.

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HR Roster Change Detection Pipeline 📝

Made With Python

an automated pipeline designed to assist HR systems in processing and analyzing roster data. Built with Apache Airflow and PostgreSQL, the system ingests roster data, detects changes (deltas), and ensures unique records are maintained. This solution streamlines roster management for organizations by automating data processing and change detection.


💎 Features

  • Integration with HR Tools: Send processed data to HR management systems.
  • Data Deduplication: Ensures only unique records are retained.
  • Enhanced Reporting: Add analytics for detailed roster insights.
  • Scalable & Reliable: Designed for high-volume roster data processing.

🔋 Tech Stack

  • Python: Core language for custom tasks and SQL execution in the pipeline.
  • Apache Airflow: Orchestrates and automates the ETL pipeline.
  • PostgreSQL: Serves as the data warehouse for roster records.

🌟 Usage Scenarios

  • Daily HR roster processing for identifying changes.
  • Automating ETL pipelines for HR scheduling systems.
  • Ensuring roster data integrity with deduplication.

🚀 Future Roadmap

  • Integrate with HR management tools.

  • Add notification alerts for significant changes.

  • Implement advanced analytics and reporting dashboards.


🚩 Contributing

Contributions are welcome! To get started:

  • Fork this repository.

  • Create a new branch for your feature or bug fix.

  • Submit a pull request for review.


📖 License

This project is licensed under the MIT License. See the LICENSE file for details.

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The HR Roster Change Detection Pipeline is an automated solution for processing HR roster data. Leveraging Apache Airflow and PostgreSQL, it enables seamless data ingestion, deduplication, and change detection, streamlining HR operations.

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