DP-700: Microsoft Fabric Data Engineer

Become proficient in designing, building, and managing scalable data engineering solutions on Microsoft Fabric with this hands-on, instructor-led course. Learn how to integrate, transform, and optimize data workflows within the unified Microsoft Fabric analytics platform, enabling seamless data ingestion, processing, and analytics.

Explore core data engineering concepts including data pipelines, Delta Lake, OneLake, and Fabric’s advanced data workloads. Gain practical experience in implementing secure, performant, and automated data solutions that power modern analytics and business intelligence.

This course offers 40% to 50% hands-on exercises, allowing participants to practice data engineering skills in Microsoft Fabric environments.

Target Audience:

This course is ideal for:

• Data engineers, data architects, and analytics professionals working with Microsoft Fabric

• IT professionals responsible for data integration, transformation, and governance

• Those preparing for certifications focused on data engineering in Microsoft Fabric

• Anyone interested in mastering data workflows and engineering within a modern cloud platform

Prerequisites:
Familiarity with SQL, data engineering principles, and cloud data concepts is recommended. Experience with Azure or big data tools is beneficial.

Course Outline:

Module 1: Introduction to Microsoft Fabric for Data Engineering

• Understand Microsoft Fabric’s architecture and unified data platform

• Explore OneLake as a central data lake and data storage foundation

• Review data engineering workloads available in Microsoft Fabric

Module 2: Designing and Implementing Data Pipelines

• Build scalable data ingestion pipelines for batch and streaming data

• Use Spark and Fabric’s integrated notebooks for data transformation

• Manage data quality, schema enforcement, and data versioning with Delta Lake

Module 3: Optimizing Data Storage and Processing

• Design data models for performance and scalability in Fabric lakehouses

• Implement partitioning, caching, and indexing strategies

• Manage compute resources for cost-effective data processing

Module 4: Securing Data Engineering Workloads

• Apply role-based access control (RBAC) and data encryption

• Configure access policies and auditing within Microsoft Fabric

• Understand compliance features and governance best practices

Module 5: Automating and Monitoring Data Engineering Solutions

• Schedule and automate workflows with Fabric orchestration tools

• Monitor pipeline performance, troubleshoot issues, and optimize throughput

• Integrate alerts and notifications for proactive operations

Module 6: Integrating Data Engineering with Analytics and BI

• Connect data engineering outputs to Power BI and Synapse analytics

• Enable self-service BI through well-prepared data pipelines

• Support data science and AI workloads with curated datasets

Delivery Format:

• Instructor-led training with expert demonstrations

• 40% to 50% hands-on labs and exercises within Microsoft Fabric environments

• Real-world scenarios designed to build practical data engineering skills