End-to-End Practical with Azure Data Engineering Tools | Complete Data Engineering Workflow

In this video, we dive deep into the end-to-end process of a data engineering project using Azure Data Engineering Tools. From data ingestion to transformation and orchestration, we cover the entire workflow, providing hands-on experience with the best Azure tools for data engineering.

What you'll learn:

Data Ingestion with Azure Data Factory (ADF)
Data Storage options in Azure (SQL, Blob Storage, Data Lake)
Data Transformation using Azure Databricks and Azure Synapse
Data Orchestration and automation with Azure Logic Apps and ADF
Data Monitoring and Troubleshooting best practices
Real-life examples and practical tips for implementing Azure data solutions
By the end of this video, you'll have a complete understanding of the tools and techniques used to build a scalable, production-ready data pipeline in Azure. Whether you're just starting out or looking to level up your skills, this practical guide will help you master the Azure data engineering ecosystem.

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👉 Timestamps:
00:00 Introduction
03:00 Setting up Data Ingestion with ADF
12:00 Storing Data in Azure
22:30 Transforming Data with Databricks
35:00 Orchestrating Workflows with Logic Apps
42:00 Monitoring and Troubleshooting Azure Pipelines
50:00 Real-World Use Cases and Next Steps
55:00 Conclusion