ELT-Data-Pipeline 🚀

ELT Data Pipeline Project implementation in Data Warehousing environment using DBT, Airflow, PostgreSQL and more!! ⚡

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📕 What is covered in this project?

• Data Orchestration: Apache Airflow
• Data Processing: Apache Spark
• On-Premise Data Lake: MinIO (Object Storage), Hive Metastore (Metadata Layer)
• Query Engine: Trino, DBeaver
• Data Warehousing: PostgreSQL
• Data Governance and Data Quality (Staging Area): Great Expectations
• Data Transformaton and Data Modeling (Star Schema): DBT (Data Build Tool) 🌟
• Data Visualization: PowerBI 📊
• ELT Data Processing Terminology Implemention

⛅ API Data Source

In this project, we will take a look at OpenAQ API, read the document here: https://openaq.org/. Specifically, we will explore the location measurement of air quality of different locations/ countries in the world. Take a look on how to create your API Key: https://docs.openaq.org/using-the-api/quick-start

🛠️ System Architecture

📁 Repository Structure

ELT-Data-Pipeline/
├── .env                      / Environment variables /
├── .git/
├── .gitignore
├── .idea/
├── Dockerfile
├── LICENSE
├── Note.txt
├── README.md
├── CHANGELOG.md
├── airflow/                  / Airflow configuration and DAGs /
│   ├── README.md
│   ├── dags/
│   │   ├── pycache/
│   │   ├── .gitkeep
│   │   ├── airqualitypipelinedag.py
│   │   ├── datamigrationdag.py
│   │   └── utils/
│   │       ├── pycache/
│   │       ├── airquality_collector.py
│   │       └── migrate_data.py
│   ├── logs/
│   └── plugins/
├── airflow-docker-compose.yaml
├── data/                     / Sample or test data /
│   ├── locationairquality.json
│   └── sensorairquality.json
├── data_validation/          / Data quality check with Great Expectations /
│   ├── .gitkeep
│   ├── README.md
│   ├── gx/
│   │   ├── .gitignore
│   │   ├── checkpoints/
│   │   ├── expectations/
│   │   ├── great_expectations.yml
│   │   ├── plugins/
│   │   ├── uncommitted/
│   │   └── validation_definitions/
│   └── openaqdataquality.ipynb
├── dbt_openaq/               / dbt project for transformations and modeling /
│   ├── .gitignore
│   ├── .user.yml
│   ├── README.md
│   ├── analyses/
│   ├── dbt_packages/
│   ├── dbt_project.yml
│   ├── logs/
│   ├── macros/
│   ├── models/
│   │   └── production/
│   │       ├── dim_date.sql
│   │       ├── dim_instrument.sql
│   │       ├── dim_location.sql
│   │       ├── dim_owner.sql
│   │       ├── dim_parameter.sql
│   │       ├── dim_provider.sql
│   │       ├── dim_sensor.sql
│   │       ├── dim_time.sql
│   │       ├── factairquality_measurement.sql
│   │       └── schema.yml
│   ├── package-lock.yml
│   ├── packages.yml
│   ├── profiles.yml
│   ├── seeds/
│   ├── snapshots/
│   ├── target/
│   └── tests/
├── docker-compose.yaml
├── images/
├── requirements.txt          / Python dependencies /
├── scripts/                  / Utility scripts /
│   ├── init.py
│   ├── pycache/
│   ├── create_schema.py
│   ├── create_table.py
│   └── postgresql_client.py
├── storage-docker-compose.yaml  / Data lake components (Trino, MinIO, Hive) /
├── trino-minio/              / Trino and MinIO configuration /
│   ├── conf/
│   │   └── metastore-site.xml
│   └── etc/
│       ├── catalog/
│       │   └── minio.properties
│       ├── config.properties
│       ├── jvm.config
│       ├── log.properties
│       └── node.properties
└── venv/

⚙ Workflow Diagram

🔥 NOTE

The Project is still in progress, so stay tuned!! 🙌🏻