Azure End-To-End Data Engineering Project | ADF • Databricks • PySpark • Medallion Architecture скачать в хорошем качестве

Azure End-To-End Data Engineering Project | ADF • Databricks • PySpark • Medallion Architecture

Azure End-To-End Data Engineering Project | ADF • Databricks • PySpark • Medallion Architecture 🚀 In this job-ready, hands-on project, i will build a complete Azure Data Engineering pipeline from scratch using Azure Data Factory, Azure Databricks, Delta Lake, and PySpark. This project follows the Medallion Architecture (Bronze, Silver, Gold) used in real enterprise data platforms and teaches me every stage of designing, ingesting, transforming, and modeling data. 🌐⚡ What You Will Learn: Data Architecture and Medallion Design 🏗️ Understand Bronze, Silver, and Gold layers, how data flows across Azure services, and why this architecture is used in real-world systems. Data Ingestion with Azure Data Factory 🔄 Create dynamic pipelines, handle incremental loads, and work with real-time ingestion scenarios. Data Lake and Azure SQL Setup 🗂️ Build Azure resources including Data Lake Gen2, containers, folder structures, and SQL Server for metadata storage. Data Transformation in Azure Databricks ⚙️✨ Use PySpark and Delta Lake to clean, transform, normalize, and optimize data. Implement Delta Tables, Unity Catalog governance, and scalable Spark clusters. Dimensional Modeling and SCD Type 2 🧩 Build fact and dimension tables, generate surrogate keys, and implement slowly changing dimensions for analytical data models. Workflows and Orchestration 📅 Use Databricks Workflows and ADF pipelines to orchestrate end-to-end data movement across Bronze, Silver, and Gold layers. End-to-End Flow: API Source → ADF Pipelines → ADLS Bronze → Databricks Silver and Gold → Star Schema → Analytics Ready Output 📈 This project is perfect for anyone preparing for Azure Data Engineer roles or building a strong cloud portfolio with real, production-ready skills. 💡🔥