Modern Data Engineering with Microsoft Fabric

Course Description

This SkillDynamo course develops practical, role-relevant capability in engineering data solutions in Microsoft Fabric with OneLake, lakehouses, notebooks, Dataflows Gen2, pipelines, Delta tables, governance, and monitoring. The learning path progresses from essential concepts and planning to implementation, validation, troubleshooting, and operational use.

Learners work through realistic scenarios, guided demonstrations, applied exercises, and evidence-based reviews. Every topic is connected to workplace responsibilities, common risks, quality controls, and measurable outcomes.

The course helps professionals make informed decisions, identify failure points, communicate results, and create an actionable improvement plan for future projects.

What You Will Learn

• Explain Fabric capacities, workspaces, OneLake, lakehouses, warehouses, notebooks, dataflows, pipelines, and integration points
• Design workspace, naming, domains, storage, access, lifecycle, development, and deployment standards
• Ingest files, databases, APIs, shortcuts, events, and cloud sources with pipelines, Dataflows Gen2, and notebooks
• Implement schemas, transformations, incremental loads, validation, merge, error handling, and medallion architecture
• Create and optimize Delta tables, partitions, maintenance, SQL endpoints, lakehouse queries, and reusable data products
• Serve data to warehouses, semantic models, Power BI, data science, real-time workloads, and approved consumers
• Apply workspace roles, item permissions, data protection, lineage, endorsement, sensitivity, domains, and governance
• Monitor capacity, pipeline runs, refreshes, failures, performance, costs, quality, incidents, and improvement actions

SkillDynamo Training Approach

SkillDynamo delivers this course through demonstrations, hands-on exercises, scenario analysis, validation checklists, structured troubleshooting, solution reviews, and a final improvement plan. Learners repeatedly practice planning, implementation, evidence collection, testing, correction, and communication so the skills transfer confidently into real workplace situations.