Azure Data Engineering Project | End to End ADF ETL Pipeline | Uber Eats Case Study — Part 1

🚀 Uber Eats End-to-End Azure Data Engineering Project 00:00 - Introduction 00:10:58 - Linked Services 00:17:53 - Resource Group Configuration 00:20:25 - ADLS Gen2 Data Lake Configuration 00:32:40 - Azure SQL Configuration Explained 00:38:34 - Building the SQL Source System Initial Load Pipeline 00:59:56 - Control & Metadata Table Explanation for SQL Source System 01:05:56 - Metadata-Driven Implementation for SQL Source System 01:32:46 - SQL Source System Incremental Processing Pipeline 01:42:52 - Azure Logic Apps Configuration 01:54:11 - On-Premises CSV File Migration 01:57:20 - SHIR Configuration for On-Premises Data Source 02:11:27 - REST API Data Migration Pipeline In this project, I built an end-to-end Azure Data Engineering pipeline for an Uber Eats–style food delivery platform. This project demonstrates how to ingest data from multiple source systems, process it using Azure services, and implement initial, batch, and incremental data loading. 🏗️ Technologies Used Azure Data Factory (ADF) Azure Data Lake Storage Gen2 (ADLS Gen2) Azure SQL Database Azure Key Vault REST APIs CSV Files Self-hosted Integration Runtime Azure Logic Apps GitHub Python 📥 Data Sources SQL Customers Restaurants Menu Items Orders Order Items CSV Drivers Promotions Zones REST API Payments Deliveries Ratings Order Status 🔄 Data Engineering Concepts Covered Initial / Full Load Batch Processing Incremental Loading Watermark-based Incremental Load Metadata-driven Pipelines Control Tables REST API Ingestion Azure Key Vault Security Success & Failure Notifications GitHub Integration 📂 Project Materials & Datasets All project materials and datasets are available in my GitHub repository. The repository contains the datasets, ADF pipelines, linked services, datasets, integration runtime configuration, SQL resources, API files, metadata, and other project materials required to follow along with this project. 👉 GitHub Repository: https://github.com/srirama9908-lang/U... 📌 Please follow the GitHub repository along with the video to access all the materials and datasets used in this project. ⭐ If you find this project helpful, please Star the GitHub repository and Subscribe to the channel for more Azure Data Engineering projects! 🎯 What You'll Learn By following this project, you will learn how to build a practical, end-to-end Azure Data Engineering solution using ADF, ADLS Gen2, Azure SQL, REST APIs, Key Vault, Logic Apps, and GitHub. This project is designed as a hands-on portfolio project for Azure Data Engineers and demonstrates practical data engineering concepts used in real-world cloud data pipelines. 🏷️ Hashtags #Azure #AzureDataFactory #DataEngineering #AzureDataEngineer #ADF #ADLSGen2 #AzureSQL #AzureKeyVault #RESTAPI #DataLake #ETL #ELT #IncrementalLoad #BatchProcessing #CloudDataEngineering #DataEngineer #MicrosoftAzure #GitHub