Microsoft Fabric

Build a complete understanding of Microsoft Fabric and the architecture behind modern data engineering and analytics platforms.

Modern organizations work with data coming from databases, files, SaaS applications, APIs, event streams, IoT devices, and many other systems. Building a platform that can reliably ingest, transform, govern, analyze, and deliver this data requires more than knowing individual tools.

Microsoft Fabric: A Complete Guide for Modern Data Engineering and Analytics provides a practical, architecture-focused introduction to building modern data platforms with Microsoft Fabric.

Starting with the fundamentals of Microsoft Fabric and OneLake, the book progressively explores data integration, Lakehouse architecture, Spark and PySpark, data warehousing, real-time intelligence, semantic modeling, Power BI, governance, security, monitoring, and production architecture.

Inside this book, you will learn how to:

- Understand Microsoft Fabric and its modern analytics architecture
- Use OneLake as a unified data foundation
- Design Lakehouse architectures using Bronze, Silver, and Gold layers
- Build data ingestion and orchestration pipelines
- Process large datasets with Spark and PySpark
- Design analytical data warehouses with SQL
- Build batch, incremental, and CDC-based data pipelines
- Work with real-time events and streaming architectures
- Understand Eventstreams, Eventhouse, and KQL
- Implement data quality, governance, security, and lineage
- Monitor production data pipelines and platforms
- Build semantic models for analytics
- Connect trusted data with Power BI
- Understand how modern data platforms support AI workloads
- Apply CI/CD, reliability, performance, and cost optimization principles
- Design an end-to-end enterprise Microsoft Fabric architecture

Rather than approaching Fabric as a collection of independent services, this book shows how its major capabilities can work together as a complete data ecosystem.

From raw data arriving from operational systems to trusted business information consumed through analytics, BI, real-time applications, and AI, the focus remains on one question:

How do we engineer a reliable modern data platform from end to end?

This book is suitable for data engineers, analytics engineers, cloud professionals, developers, architects, students, and technology professionals