Mastering Azure Data Engineering: Part 4 – Azure Skills

Mastering Azure Data Engineering continues with Part 4, focusing on advanced Azure skills crucial for proficient data engineering. This module delves into integrating Azure Blob storage with SQL databases, automating table creation, parameterization techniques, stored procedure activities, and data transformation using derived columns. Participants will engage in step-by-step tutorials, hands-on labs, and practical exercises to solidify their understanding and expertise in these essential Azure Data Factory functionalities. By the end of the course, learners will possess the skills necessary to streamline data integration, automation, and transformation processes within Azure Data Factory, empowering them to tackle complex data engineering challenges with confidence.

Course Objectives:

1. Master the process of integrating Blob storage with SQL databases in Azure Data Factory.
2. Automate table creation tasks within Azure Data Factory pipelines for enhanced efficiency.
3. Implement parameterization techniques to enhance flexibility and reusability in data workflows.
4. Utilize stored procedure activities effectively for executing database operations within Azure Data Factory.
5. Learn how to transform data using derived columns, enabling advanced data manipulation capabilities.
6. Efficiently filter data using the Select All activity in Azure Data Factory to optimize data processing workflows.

Target Audience:

• Experienced Data Engineers
• Data Architects
• Azure Developers
• IT Professionals seeking advanced Azure data engineering skills

Prerequisites:

• Proficiency in Azure Data Factory fundamentals.
• Familiarity with SQL databases and data transformation concepts.
• Basic understanding of Azure services and cloud computing principles.

Delivery Format:

• Instructor-led training sessions
• Hands-on labs and tutorials