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This project demonstrates an end-to-end solution for real-time data streaming and analysis using Azure Databricks and Azure Event Hubs, with visualization in Power BI. It's an in-depth guide covering the setup, configuration, and implementation of a streaming data pipeline following the medallion architecture.

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Real-Time-Streaming-with-Azure-Databricks

Project Overview

Welcome to the "Real-Time Streaming with Azure Databricks" repository. This project demonstrates an end-to-end solution for real-time data streaming and analysis using Azure Databricks and Azure Event Hubs, with visualization in Power BI. It's an in-depth guide covering the setup, configuration, and implementation of a streaming data pipeline following the medallion architecture.

Data Model

Getting Started

To get started with this project, clone the repository and follow the guidance provided in this YouTube tutorial.

Repository Contents

  • Real-time Data Processing with Azure Databricks (and Event Hubs).ipynb: The Databricks notebook used for data processing at each layer of the medallion architecture.
  • data.txt: Contains sample data and JSON structures for streaming simulation.
  • Azure Solution Architecture.png: High level solution architecture.

Prerequisites

  • Active Azure subscription with access to Azure Databricks and Event Hubs.
  • Databricks Workspace with Unity Catalog Enabled.
  • Azure Event Hubs Service.
  • Power BI Desktop (Windows).
  • Familiarity with Python, Spark, SQL, and basic data engineering concepts.

About

This project demonstrates an end-to-end solution for real-time data streaming and analysis using Azure Databricks and Azure Event Hubs, with visualization in Power BI. It's an in-depth guide covering the setup, configuration, and implementation of a streaming data pipeline following the medallion architecture.

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  • Jupyter Notebook 100.0%