Realtime Streaming End to End Azure Data Engineering Project

Build a robust real-time data pipeline on Azure with this practical, hands-on project. Learn to create a production-ready system for streaming data, from initial data ingestion to interactive live dashboards.

This course guides you through the entire process of building a streaming ETL pipeline using key Azure services. You'll ingest Live Weather API events via two methods: Databricks PySpark and Azure Functions. These events will be published to Azure Event Hubs, then processed using Microsoft Fabric Eventstream. Finally, the processed data lands in Eventhouse (Kusto) for fast querying and analysis. Visualize your insights with Power BI and set up real-time alerts using Data Activator.

You'll gain expertise in:

• Azure Environment Provisioning: Learn how to correctly set up essential components including Resource Groups, Databricks workspace/cluster, Event Hubs namespace & hub, Key Vault, and Fabric workspace.
• Secure Secret Management: Implement best practices for securely managing sensitive information.
• Reliable Streaming Architecture: Connect and configure services to create a dependable streaming architecture.
• Kusto Query Language (KQL): Write efficient KQL queries for rapid data analysis within Eventhouse.
• Cost Optimization: Apply cost-effective strategies for configuring clusters, Throughput Units, and storage to minimize expenses.

By the end of this project, you will be able to:

• Design scalable Azure streaming architectures.
• Implement data ingestion using both Databricks (PySpark) and Azure Functions.
• Stream data into Event Hubs and route it effectively with Fabric Eventstream.
• Load and query data efficiently in Eventhouse using KQL.
• Develop interactive live Power BI dashboards and configure alerts with Data Activator.
• Monitor, troubleshoot, and optimize your pipeline for both cost and performance.
• Conduct end-to-end pipeline testing, ensuring data flows seamlessly from ingestion to reporting.

This project is ideal for anyone looking to gain a clear, practical understanding of building streaming ETL pipelines for real-world applications on Azure. Perfect for aspiring data engineers, data scientists, and anyone working with real-time data.