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Sensor Data ELT

A fully dockerized ELT pipeline project, using Postgres, MYSQL, dbt, Apache Airflow, Redash and Superset.
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Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgements

About The Project

Product Name Screen Shot

A fully dockerized using a docker-compose file ELT pipeline using MySQL, PostgreSQL, Airflow, DBT, Redash and Superset. used MySQL and Postgres for data ware house. used DBT for data transforming and airflow for automation and orchestrations. A redash and Superset dasboard is built by connecting it to our data ware .

Built With

Tech Stack used in this project

Getting Started

Prerequisites

Make sure you have docker installed on local machine.

  • Docker
  • DockerCompose

Installation

  1. Clone the repo
    git clone https://github.com/daniEL2371/sensor-data-ELT.git
  2. Run
     docker-compose build
     docker-compose up
  3. Open Airflow web browser
    Navigate to `http://localhost:8000/` on the browser
    activate and trigger load_data dag
    activate and trigger migrate_data dag
    activate and trigger dbt_dbt_dag
  4. Access your Postgres database using adminar
    Navigate to `http://localhost:8080/` on the browser
    use `postgres` databse
    use `postgres-dbt` server
    use `dbtuser` for username
    use `pssd` for password
  5. Access redash dashboard
    open new terminal
    docker-compose run — rm server create_db
    Open pstgres-dbt using adminar
    Create a user for analytics database
    CREATE USER 'redash'@'' IDENTIFIED WITH mysql_native_password BY 'root';
    Grant all privilages for analytics database
    GRANT ALL PRIVILEGES ON analytics.* To 'redash'@'';
    Navigate to `http://localhost:5000/` on the browser
    Login and use your created user on analytics databse to connect to your databse
  6. Access Superset dashboard
    Navigate to `http://localhost:8088/` on the browser
    use `root` for username
    use `roor` for password

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Daniel Zelalem - danielzelalemheru@gmail.com

Acknowledgements

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