Welcome to AnalytixCloud, In this hands-on tutorial, we'll dive into a real-time project on Azure Data Engineering. Whether you're an experienced data engineer looking to expand your skills or a newcomer to Azure, this project will provide you with valuable insights and practical experience.

In this video, we'll cover:

1. Project Overview:
Introduction to the real-time project we'll be building on Azure.

2. Azure Services Used:
Explanation of the Azure services and tools we'll utilize in this project, including Azure Data Factory, Azure Data Lake Storage, Azure Databricks, and PowerBI.

3. Data Ingestion:
Demonstrating how to ingest data in real-time from various sources using Azure Data Factory and set up data pipelines.

4. Data Transformation:
Showing how to clean, transform, and enrich the incoming data streams using Azure Databricks.

5. Data Storage:
Discussing best practices for storing real-time data efficiently using Azure Data Lake Storage and Azure Databricks as delta tables.

6. Visualization:
Creating meaningful visualizations using Power BI to gain insights from the processed data.

7. Deployment & Scaling:
Demonstrating how to deploy and scale your Azure data solution as needed to meet growing demands.

8. Best Practices & Tips:
Sharing best practices, tips, and lessons learned throughout the project.

9. Conclusion:
Summarizing the key takeaways and the importance of Azure Data Engineering in today's data-driven world.

You can also visit our website for our courses: [ Ссылка ]
Mob: +91-7411310205
Telegram: [ Ссылка ]
Whatsapp: [ Ссылка ]

Please support us for more videos: [ Ссылка ]

Don't forget to like, subscribe, and hit the notification bell to stay updated with our latest Azure and data engineering tutorials. If you have any questions or need further clarification on any topic covered in this video, please feel free to leave a comment below, and we'll be happy to assist you.

Thank you for watching, and let's dive into the world of Azure Data Engineering together!

свернуть