Overview

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This course provides a comprehensive guide to Microsoft Fabric, focusing on building scalable, secure, and AI-driven data solutions. It covers essential tools and techniques for modern data analytics, helping professionals harness the power of Microsoft Fabric. By integrating Copilot, the course enhances developers' productivity while tackling real-world data use cases. Learners will build complete data analytics systems, from data integration to transformation and visualization. With hands-on, scenario-based tutorials, the course prepares students to create systems for lakehouses, data warehouses, real-time analytics, and data science. The course blends theoretical concepts with practical applications, ensuring learners gain real-world experience in building future-ready data solutions. Key features include learning through real-world examples and understanding how to monitor, manage, and secure data environments. Designed for data professionals with a basic understanding of SQL and Spark, this course helps analysts, engineers, scientists, and developers advance their skills in AI-driven analytics. Based on the book, Learn Microsoft Fabric, by Arshad Ali and Bradley Schacht.

Syllabus

Overview of Microsoft Fabric and Understanding Its Different Concepts

This section introduces Microsoft Fabric as a unified analytics platform, focusing on its core capabilities and how it simplifies data management.

Understanding Different Workloads and Getting Started with Microsoft Fabric

In this section, we explore Microsoft Fabric workloads, including Data Factory, Data Engineering, and Real-Time Analytics, to build end-to-end analytics systems with practical applications.

Building an End-to-End Analytics System Lakehouse

In this section, we explore building an end-to-end analytics system using a lakehouse architecture with Medallion layers, Delta Lake, and OneLake for unified data storage and analysis.

Building an End-to-End Analytics System Data Warehouse

In this section, we explore building an end-to-end analytics system using a data warehouse, focusing on data ingestion, T-SQL transformation, and ETL orchestration with Data Factory for practical data processing and reporting.

Building an End-to-End Analytics System Real-Time Analytics

In this section, we explore real-time analytics systems, focusing on data pipelines, Kusto Query Language, and Power BI reporting for scalable data solutions.

Building an End-to-End Analytics System Data Science

In this section, we explore building an end-to-end analytics system using AI and ML, focusing on data ingestion, model design with LightGBM and FLAML, and operationalizing models in Microsoft Fabric.

Monitoring Overview and Monitoring Different Workloads

This section covers monitoring Data Factory, Spark, and real-time analytics in Fabric for improved performance and reliability.

Administering Fabric

In this section, we explore enabling Microsoft Fabric in a tenant, managing Spark job configurations, and associating capacities with workspaces for efficient resource allocation and performance optimization.

Security and Governance Overview

In this section, we examine Microsoft Fabric's security and governance frameworks, focusing on platform protection, workspace permissions, and compliance strategies to ensure data integrity and regulatory adherence.