Build Real-Time E-Commerce Data Lake&Analytics Platform Using Spring + Kafka+AWS S3+Apache Airflow скачать в хорошем качестве

Build Real-Time E-Commerce Data Lake&Analytics Platform Using Spring + Kafka+AWS S3+Apache Airflow

🌊 Data Lake Medallion Architecture 🚀 Learn how to build a production-grade Data Lake from scratch! This project covers everything from real-time events to business-ready dashboards. 📂 GitHub Repo: https://github.com/nithinraaj27/Datalake 🛒 The Ingredients (Tech Stack) ⚡ Data Ingestion: Apache Kafka, Spring Boot (Java 17), Python 📦 Storage: Amazon S3 (Bronze, Silver, Gold Layers) 🪄 Processing: AWS Glue Crawlers & Amazon Athena (SQL) 🌬️ Orchestration: Apache Airflow (Dockerized) 📊 Analytics: Metabase via Athena JDBC 🐳 Platform: Docker & Docker Compose 👨‍🍳 The Recipe (How it works) Prep: Python produces mock events into Kafka. Cook: Spring Boot consumes the data and saves it to the S3 Bronze layer. Refine: Airflow triggers Glue Crawlers to discover schemas. Simmer: Athena CTAS queries transform Raw (Bronze) → Clean (Silver) → Aggregate (Gold). Serve: Metabase pulls the Gold data for beautiful, real-time dashboards. 📌 Timestamps 0:00 Architecture Overview 3:40 Project Setup 5:51 Airflow DAG Orchestration 13:21 Project/Folder Structure Explanation 16:21 Metabase Setup #DataEngineering #AWS #Kafka #Airflow #BigData #SpringBoot #Python #DataLake #spring #springboot