End-to-End Flight Operations Data Engineering Project using Airflow скачать в хорошем качестве

End-to-End Flight Operations Data Engineering Project using Airflow

🔥 End-to-End Flight Operations Data Engineering Project using Apache Airflow 🔥 In this video, I build a real-world, end-to-end data engineering project using Apache Airflow, where we ingest live flight data from a real public API, process it using Medallion Architecture (Bronze, Silver, Gold), and deliver near-real-time analytics ready for BI dashboards. This project is designed to demonstrate how Airflow is actually used in production — not just DAG syntax, but orchestration, scheduling, retries, idempotent pipelines, and analytics-ready data modeling. If you’re preparing for data engineering, analytics engineering, or Airflow-focused roles, this project is a strong portfolio addition. 🚀 What You’ll Learn In this hands-on project, you’ll learn how to: • Pull live flight operations data from a real external API • Build a fully automated Airflow pipeline running on a schedule • Implement Medallion Architecture: Bronze: raw API JSON ingestion Silver: cleaned & normalized flight data Gold: aggregated flight KPIs • Design time-windowed, incremental analytics tables • Load analytics data into PostgreSQL using UPSERT logic • Build rerunnable, failure-safe Airflow DAGs • Handle retries, dependencies, and task orchestration properly • Prepare data for near-real-time BI dashboards (Power BI ready) • Think like a production data engineer, not a tutorial follower 🧠 Project Use Case This project simulates how aviation analytics and operations teams analyze global flight activity patterns — not individual flights — to: • Monitor air traffic volume trends • Detect congestion signals • Compare activity across countries and time windows • Build historical, analytics-ready datasets from live data The goal is pattern-level monitoring and analytics, not air-traffic control. 🧰 Tech Stack Used Apache Airflow Python Snowflake REST API (Live Flight Data) Docker & Docker Compose Medallion Architecture (Bronze → Silver → Gold) Power BI (optional) 📊 Project Highlights • Real API ingestion (no fake data, no CSV downloads) • Near-real-time batch processing (30-minute windows) • Proper separation of raw, cleaned, and analytics layers • Incremental, historical KPI storage • Production-style orchestration and data modeling • Clean, modular, portfolio-ready codebase 🗂 GitHub Repository https://github.com/Jay61616/flight-op... API Data Format: https://openskynetwork.github.io/open... 🕒 Timestamps 0:00 Intro 0:38 Project Overview 6:05 Repo initialize 11:48 Airflow Installation 36:38 Bronze transformation 1:16:44 Silver transformation 1:46:39 Gold transformation 2:07:57 Load data to Snowflake 2:17:51 Initialize Snowflake 2:46:23 Dashboarding 📣 Let’s Connect LinkedIn:   / jayachandrakadiveti   GitHub: https://github.com/Jay61616 Website: https://jay.unaux.com Credits: Intro Music: https://socialbunnymarketing.com Icons: https://www.flaticon.com/ 🎯 Hashtags #ApacheAirflow #DataEngineering #AirflowProject #ETLProject #MedallionArchitecture #DataPipeline #PortfolioProject #Python #PostgreSQL #PowerBI #AnalyticsEngineering