Microsoft's skills measured for DP-700 as of October 19, 2026, mapped to the chapters of Ultra Transcenders DP-700: Implementing Data Engineering Solutions Using Microsoft Fabric.
| Objective | Chapters |
|---|---|
| Implement and manage an analytics solution (30–35%) | |
| Configure Microsoft Fabric workspace settings | 1. Microsoft Fabric for data engineers: platform, capacities and choosing a data store; 2. Workspace settings for Spark, domains, OneLake and Apache Airflow |
| Implement lifecycle management in Fabric | 3. Lifecycle management: Git, database projects and deployment pipelines |
| Configure security and governance | 4. Securing data: workspace, item, row, column, object and file access; 5. Governance: sensitivity labels, endorsement and audit logs |
| Orchestrate processes | 6. Orchestrating with pipelines, notebooks and Dataflow Gen2 |
| Ingest and transform data (30–35%) | |
| Design and implement loading patterns | 7. Loading patterns: full, incremental, dimensional and streaming |
| Ingest and transform batch data | 1. Microsoft Fabric for data engineers: platform, capacities and choosing a data store; 7. Loading patterns: full, incremental, dimensional and streaming; 8. Batch ingestion: shortcuts, mirroring, pipelines and Copy job; 9. Transforming data with PySpark and Spark SQL; 10. Transforming data with T-SQL and KQL |
| Ingest and transform streaming data | 10. Transforming data with T-SQL and KQL; 11. Real-Time Intelligence: engines, eventstreams and eventhouses; 12. Stream processing with Spark structured streaming, KQL and windowing |
| Monitor and optimize an analytics solution (30–35%) | |
| Monitor Fabric items | 13. Monitoring and alerts |
| Identify and resolve errors | 14. Identifying and resolving errors |
| Optimize performance | 15. Optimising performance |
The full list of tasks under each objective is in the official DP-700 study guide and practice assessment. The book is organised by technology, so one chapter often serves several objectives.