Microsoft Azure - Data Lake

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Overview

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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

Syllabus

Foundations of Azure Data Lake

This module introduces learners to the core concepts and foundational setup of Microsoft Azure Data Lake. It explores the motivation behind using data lakes in the era of big data, the components that make up the Azure Data Lake ecosystem, and walks learners through setting up an analytics account and essential services. By the end of the module, learners will have a conceptual and practical understanding of Azure Data Lake’s architecture and its role in modern data processing workflows.

Mastering USQL and Data Processing

This module delves into the fundamentals and practical applications of U-SQL within Azure Data Lake Analytics. Learners will gain a thorough understanding of how to write and optimize U-SQL scripts, manage Analytics Units for performance tuning, and apply filtering techniques to datasets. The module also introduces learners to U-SQL job execution stages, the structure and syntax of U-SQL language, and schema handling concepts such as "Schema on Read". By the end of this module, learners will be able to write, execute, and interpret U-SQL scripts effectively within real-world big data scenarios.

Data Aggregation and File Handling

This module focuses on handling larger volumes of data in Azure Data Lake by exploring aggregation techniques, multi-file ingestion, and distributed processing methods using U-SQL. Learners will develop the ability to group and summarize data effectively, troubleshoot aggregation logic, ingest and process multiple structured files, and understand various data distribution strategies such as hash, range, and round-robin. By the end of this module, learners will be equipped to manage and transform scalable datasets using advanced features of Azure Data Lake Analytics.

Advanced Query Development

This module explores advanced techniques for querying and managing data within Azure Data Lake using U-SQL. Learners will gain hands-on experience working with structured objects such as views, table-valued functions, and stored procedures, while also incorporating inline C# functions for enhanced query logic. The module emphasizes reusability, modular design, and dynamic data manipulation strategies to improve analytical workflows in real-world data lake environments.

Development and Job Monitoring

This module guides learners through developing, deploying, and monitoring U-SQL jobs using Visual Studio and Azure Data Lake Analytics. It introduces project setup, job submission, and custom code integration using Visual Studio tools. Learners will explore job diagnostics, performance analysis with job graphs and heat maps, and advanced debugging with the vertex execution view. The module concludes with tools for evaluating job efficiency and identifying execution bottlenecks, empowering users to optimize big data workflows.

Data Store Management and Pricing

This module provides a comprehensive overview of accessing, managing, and organizing data within Azure Data Lake using both graphical and command-line tools. Learners explore various access methods including Azure CLI and PowerShell, understand how to create, upload, and manage files and directories in the Data Lake Store, and perform operations such as renaming and deleting accounts. The module also explains Azure Data Lake pricing models and ends with a concise summary to reinforce best practices and service structure.