Learn Microsoft Fabric architecture, semantic modeling, DAX, security, lakehouses, pipelines, Spark, SQL, KQL, deployment, lifecycle management, Power BI in Fabric, and exam-focused practice.
In DP-600 Exam Course, Greg Trzeciak helps learners prepare for the Microsoft DP-600 exam by walking through the major skills needed to design, implement, secure, and maintain analytics solutions in Microsoft Fabric. This course is built around the core exam areas, including Fabric architecture, semantic modeling, DAX, security, deployment, lakehouses, pipelines, dataflows, Spark, SQL, KQL, lifecycle management, and Power BI experiences in Fabric.
Throughout the course, learners will review important exam concepts, see practical demonstrations, and work through practice question sections designed to reinforce key topics. The course also includes exam orientation, Microsoft Learn guidance, CertXP preparation, and a capstone-style review to help learners connect individual skills into a complete Fabric analytics workflow. By the end, learners will have a stronger understanding of DP-600 exam expectations and how Microsoft Fabric components work together in real-world analytics solutions.
Course Outline ( Free Preview)
Module 01 - Introduction
Greg introduces the DP-600 exam course and helps learners understand how to approach exam preparation. This module covers orientation, exam structure, scoring, CertXP, practice questions, and how to use Microsoft Learn as a study resource. Learners will leave with a clearer plan for navigating the course and preparing for the certification exam.
Module 02 - Fundamentals of Fabric20 min.
Learn the foundational architecture of Microsoft Fabric and how its major components fit together. Greg explains the core Fabric concepts learners need before moving into modeling, engineering, security, and analytics scenarios. This module establishes the platform-level context needed to understand how Fabric supports end-to-end analytics solutions.
Module 03 - Data Modeling Concepts133 min.
Explore the modeling concepts that are central to DP-600 preparation, including semantic model foundations, advanced modeling techniques, DAX essentials, calculation groups, field parameters, and optimization. Greg also covers how to think about DAX performance and model quality so learners can build more reliable analytics solutions. This module helps learners connect model design, calculations, and performance to exam-style scenarios.
Module 04 - Security and Deployment96 min.
Learn how security and deployment concepts apply across Microsoft Fabric workspaces and data items. This module covers workspace-level access, item-level access, row-level security, column-level security, object-level security, file-level controls, sensitivity labels, endorsements, and related practice questions. Learners will understand how to apply governance and access controls in ways that align with Fabric administration and exam expectations.
Module 05 - Data Preparation and Engineering156 min.
Explore the data engineering and preparation skills needed for the DP-600 exam. This module covers lakehouse ingestion, Dataflow Gen2, pipelines, SQL and KQL querying, Spark notebooks, transformations, lakehouse vs. warehouse vs. eventhouse decisions, joins and merges, views, functions, stored procedures, OneLake integration, and eventhouse creation. Learners will see how Fabric supports data movement, transformation, and querying across multiple workloads.
Module 06 - Maintain the Analytics Development Lifecycle67 min.
Learn how to manage the analytics development lifecycle in Microsoft Fabric. This module covers version control, Power BI Desktop projects, deployment pipelines, downstream dependency impact analysis, XMLA endpoint usage, reusable assets, Direct Lake configuration, incremental refresh, and external tools like DAX Studio and Tabular Editor. Learners will understand how to maintain, deploy, and manage analytics assets more effectively across environments.
Module 07 - Data Analysis and Visualization20 min.
Explore how Microsoft Fabric supports data analysis and visualization through Power BI and related experiences. This module includes visualizing SQL query results, using the Visual Query Editor, and reviewing Power BI in Fabric practice scenarios. Learners will connect prepared data and semantic models to reporting and analysis workflows that support decision-making.
Module 08 - Conclusion2 min.
Greg wraps up the DP-600 Exam Course with final guidance for review and next steps. Learners will revisit the major course themes and understand where to focus continued study before taking the exam. This module closes the course by helping learners move from guided preparation into confident independent review.
Zane Goodman is a Consultant and Trainer at Pragmatic Works specializing in Microsoft Fabric, Databricks, Python, and modern data platform solutions. He helps organizations design, implement, and optimize scalable analytics environments that transform raw data into actionable business insights. With expertise spanning data engineering, analytics, automation, and cloud-based data architectures, Zane works closely with clients to build solutions that are both technically sound and aligned with business objectives.
As both a consultant and educator, Zane is passionate about helping organizations adopt modern data technologies and develop the skills needed to succeed with them. He frequently works with clients on Microsoft Fabric implementations, lakehouse architectures, data pipelines, notebook development, and analytics workloads, while also leveraging Databricks and Python to solve complex data challenges. Known for his practical and approachable teaching style, Zane excels at breaking down sophisticated concepts into clear, actionable guidance that empowers teams to become self-sufficient and successful.
Whether he is leading a Fabric deployment, developing custom data solutions, or delivering technical training, Zane's focus remains the same: helping organizations unlock the value of their data through modern technologies, practical learning experiences, and real-world best practices.
