This hands-on course empowers learners to design, implement, and optimize data analytics solutions using Microsoft Azure Data Lake. Through a step-by-step, modular framework, participants will explore the fundamentals of scalable data storage, master U-SQL scripting for data transformation, and gain proficiency in job submission, performance tuning, and cost management using tools like Azure CLI, PowerShell, and Visual Studio.

Learners will analyze real-world data scenarios, construct dynamic queries, deploy reusable views and functions, and evaluate job performance through diagnostics, heat maps, and vertex execution views. The course concludes with strategies to organize, secure, and manage data using both graphical and command-line tools, while also interpreting pricing models for efficient cost planning. Aligned with Bloom’s Taxonomy, this course encourages learners to: Understand the architecture and components of Azure Data Lake Apply U-SQL to perform data extraction, filtering, and aggregation Analyze job graphs and performance metrics for optimization Create reusable query logic using views, functions, and stored procedures Evaluate cost efficiency and scalability across access methods Manage data environments using automation and scripting interfaces