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Try CodeCrafters for free using my referral link: https://app.codecrafters.io/join?via=... Welcome to this beginner-friendly data engineering project where we build a live air quality dashboard from scratch using Python, Plotly Dash, and DuckDB! 🌍📊 In this tutorial, I'll take you through the entire pipeline: 1. Data Extraction: Fetching real-time air quality data from OpenAQ. 2. Data Transformation: Cleaning and processing data using DuckDB for fast and efficient handling. 3. Data Visualization: Creating a sleek and interactive dashboard with Plotly Dash. Whether you're new to data engineering or looking to sharpen your skills, this project is great for learning the basics of: • Building a functional data pipeline 🛠️ • Working with live data feeds ⏱️ • Designing interactive dashboards 🎨 🔑 Key Topics Covered: • Setting up your Python environment • Using DuckDB to manage and query data • Creating dynamic visuals with Plotly Dash • Tips and tricks for handling real-world data challenges 🗂️ Resources: • Code Repository: https://github.com/trentpark8800/air-... • Open AQ: https://openaq.org • DuckDB Documentation: https://duckdb.org • Plotly Dash: https://dash.plotly.com/ • Dbeaver: https://dbeaver.io/download/ • Bbox Finder: http://bboxfinder.com/ If you found this video helpful, don’t forget to like, comment, and subscribe for more data engineering projects! 📖 Chapters: 0:00 Intro 2:10 The OpenAQ Project 5:55 Project Setup 11:50 Location Data Extraction 26:15 DuckDB and S3 Setup 43:25 Data Quality Check 53:18 Data Product Creation 01:19:00 Plotly Dash Dashboard Setup 01:49:44 End of Part 1 01:52:19 Database Manager Script 02:26:43 Data Extraction Script 03:10:00 Data Transformation Script 03:22:46 Another Look at Data Quality 03:31:30 Refining The Dashboard 04:10:28 Testing With a New Data Point 💵SUPPORT THE CHANNEL CodeCrafters Affiliate: https://app.codecrafters.io/join?via=... Become a channel member: / @trentdoesmath Direct, once off transfers: https://www.paypal.com/paypalme/trent...