Azure Data Factory | Data Engineering on Azure and Fabric

🌟 Course Title: Azure Data Factory | Mastering Data Engineering on the Cloud (DP203)

Course Headline:

🛠️ Get Hands-On and Build a Modern Data Lake with Azure Data Factory (ADF), Data Lake Storage, Azure SQL, and More! (DP203)

Course Description:

🚀 Hello Students!

Are you ready to dive into the world of cloud-based data integration services? As the demand for professionals skilled in data engineering and analytics continues to soar, learning Azure Data Factory is not just beneficial—it's imperative! 🌱

Azure Data Factory is a key player in Microsoft Azure's suite of services, offering robust capabilities for data movement and transformation at scale. By enrolling in this course, you'll unlock the potential of Azure Data Factory and gain a competitive edge in the dynamic field of data engineering.

Throughout this course, you will engage with a rich array of learning materials, including comprehensive lectures, hands-on code-along videos, and a dedicated course project that will solidify your understanding and practical skills. Plus, you'll enjoy lifetime access to all the lectures—because learning doesn't end when the course does!

Here's what you can expect to master in this course:

Core Topics Covered:

1. 💾 Azure Storage Solutions

   • Understanding Azure Blob Storage and Azure Data Lake Gen2 Storage capabilities.

2. Azure Data Factory Basics

   • Exploring the core components such as Linked Services, Datasets, Activities (including Data Flows), Integration Runtimes, and more.

3. Data Formats Integration

   • Mastering data import from various file formats like CSV, JSON, and Parquet.

4. Copy Activity Deep Dive

   • Leveraging the Copy Activity for efficient data movement within Azure Data Factory.

5. Data Flows, Control Flow, and Transformation Activities

   • Implementing advanced data processing and orchestration techniques.

6. Orchestrating Data Integration Workflows

   • Building and managing complex workflows to automate your data integration tasks.

7. Schedules & Triggers

   • Setting up schedules and triggers for executing pipelines at the right time with the right data.

8. Parameters & Variables

   • Utilizing parameters and variables within Linked Services, Datasets, and Pipelines to create dynamic and flexible data processing solutions.

9. Azure SQL Database Integration

   • Integrating Azure Data Factory with SQL databases for seamless data operations.

10. Authentication & Access

    • Securing your data with Managed Identities, Service Principals, and Azure Key Vault.

By the end of this course, you will have a solid foundation in Azure Data Factory and its ecosystem, preparing you to build, manage, and scale modern data lakes on Microsoft Azure. 🎓

Join me, Malvik Vaghadi, in this enlightening journey through the cloud, and let's turn your passion for data engineering into a thriving career!

Sign up now and take the first step towards mastering Azure Data Factory and cloud-based data engineering! 💫