From basics to advanced techniques across data engineering, warehousing, and science within the Microsoft Fabric ecosystem
Hands-on exercises and real-life case studies to apply what you've learned directly to your work
Equip yourself with the expertise required to lead in the data-driven world, with a focus on the latest tools and technologies
Description
This course is ideal for those with a grasp of data concepts and cloud computing basics, especially in Microsoft Azure. Programming skills in SQL, Spark, and Python are beneficial but not mandatory. You'll begin with an introduction to Microsoft Fabric, delving into its objectives and success criteria, and explore the contrasting architectures of Lakehouse and Warehouse, along with insights into licensing, workspace creation, and configuration.
Progress to mastering OneLake and Delta Lake, ensuring data security with authentication and authorization, while tackling Spark's complexities, data hub management, and warehouse management. This includes everything from understanding datasets and ingestion methods to utilizing Spark for real-time data processing, exploring SQL and KQL differences, and experiencing data flow architecture and Power BI visualizations in the Data Factory.
The course concludes with a deep dive into Data Science and robust Data Management, ensuring you are equipped with the knowledge to control access, govern data, and monitor your systems effectively in any professional setting.
What you will learn
Discover the principles of data engineering in Microsoft Fabric, including Lakehouse and Delta Lake
Construct and manage data warehouses with Fabric's tools
Perform real-time analytics using SQL, KQL, and Spark
Build and execute data pipelines in the Data Factory module
Create compelling data stories through Power BI visualizations
Explore how to manage access control, governance, and monitoring in the Fabric environment
Henry Habib, a top instructor with 200K students, is a manager at a leading management consulting firm, advising Fortune 500 companies on growth strategy, operations, and analytics. With extensive experience in data-driven solutions for both large and small organizations, Henry is a champion of Generative AI and No-Code application development. He integrates these technologies to deliver efficient, comprehensible business applications. As a professor, Henry is dedicated to student success, creating engaging courses and offering continuous support on topics like case interviews, no-code development, and automation.
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