Ultimate Microsoft Fabric for Data Analytics Solutions

One Platform. Every Data Skill. One Certification That Proves It.

Key Features
● Get a free one-month digital subscription to www.avaskillshelf.com.
● Comprehensive Microsoft Fabric coverage spanning Lakehouse, Data Factory, Dataflows, Notebooks, and Power BI.
● Full DP-600 exam objective coverage with certification-oriented practice questions and exhaustive answers.
● Hands-on enterprise labs covering PySpark, Scala, SQL, OneLake, Event streams, and MLflow model tracking.

Book Description
Build the Data Platform. Engineer the Analytics. Prove Your Skills with DP-600.

Microsoft Fabric brings together data engineering, data science, real-time analytics, and business intelligence into a single unified platform — and mastering it is becoming one of the most valuable skills in modern data engineering. Ultimate Microsoft Fabric for Data Analytics Solutions is a comprehensive guide to both the platform and the DP-600 Analytics Engineer Associate certification, covering every exam objective through practical enterprise scenarios.

You begin with tenant settings and Microsoft Fabric architecture, then advance through Lakehouse design, Data Factory pipelines with low-code and code-first ETL, advanced data science workflows with MLflow model tracking, OneLake storage and shortcuts, and real-time intelligence using Event streams. Every chapter integrates hands-on labs that reflect real-world data scenarios across PySpark, Scala, and SQL environments.

The final section covers Power BI, semantic models, Copilot AI integration, and real-world case studies, before closing with DP-600 certification preparation, including practice questions that replicate the format and depth of the live exam. Thus, by the end of the book, you will build production-ready data analytics solutions on Microsoft Fabric, and pass the DP-600 exam with confidence.

What you will learn
● Design and implement end-to-end data architectures using the unified Microsoft Fabric platform.
● Build low-code and code-first ETL pipelines using Data Factory, Dataflows, and Notebooks.
● Store and manage scalable data using OneLake, Lakehouse architecture, and external shortcuts.
● Process real-time data streams using Event streams for ingestion, alerting, and intelligence.
● Develop Machine Learning (ML) workflows and track models across experiments using MLflow.
● Prepare for and pass the DP-600 certification exam using targeted practice questions and answers.

1. Getting Started with Microsoft Fabric
2. Setting up Your Microsoft Fabric Environment
3. Data Engineering Implementation
4. Data Factory Implementation
5. Advanced Data Science Experience in Microsoft Fabric
6. Lake-Centric Data Warehousing with OneLake
7. Real-Time Intelligence in Fabric
8. Analytics with Power BI and Semantic Models in Microsoft Fabric
9. Real-World Applications and Case Studies
10. Conclusion and Next Steps
Index

Shiv is a Team Lead and Senior Data Engineer with more than 8 years of experience in Data and Analytics, specializing in Microsoft Fabric, Azure, Databricks, and Agentic AI solutions.

Rajib Kumar De is a Team Manager and Lead Data Scientist with over 10 years of experience, specializing in enterprise Generative AI, Agentic AI, and Microsoft Fabric solutions, and holding an M.Sc. in Statistics.

About the Technical Reviewer

Adinath Kadam is a finance analytics professional specializing in FP&A systems design, cloud-native data architecture, and AI-assisted financial workflows. His work focuses on building scalable and governed reporting ecosystems that modernize traditional finance operations while maintaining operational flexibility and cost efficiency.

He has contributed to enterprise reporting modernization initiatives using AWS-native infrastructure, Power Query, SQL-based semantic layers, and cloud-native analytics workflows. His research explores cloud-native FP&A architecture, governed reporting systems, Excel-based transformation frameworks, and the emerging role of Large Language Models (LLMs) in financial analytics and decision support.

Adinath holds an MS in Information Systems from the Stevens Institute of Technology, and combines hands-on enterprise implementation experience with research-driven systems thinking in modern financial reporting and analytics transformation.

Jeevanram Kasiviswanathan is a software architect and technology leader with over a decade of experience designing and delivering enterprise-scale systems across multiple industries. Holding an M.Sc. in Software Engineering from PSG College of Technology, Coimbatore, he has developed deep expertise across the Microsoft ecosystem, including .NET, Azure, Microsoft Fabric, cloud-native platforms, and AI-powered solutions.

He specializes in enterprise architecture, API-first systems, data platforms, and cloud modernization, helping organizations build scalable, resilient, and AI-ready technologies. Passionate about responsible AI adoption and modern engineering practices, he focuses on creating solutions that combine innovation with strong governance and long-term scalability.

Beyond his technical work, Jeevanram is an active mentor and advocate for continuous learning, guiding engineering teams toward architectural excellence, innovation, and data-driven transformation. His work reflects a commitment to building modern technology systems that enable sustainable business growth and engineering excellence.