Can I use notes in the DP-700 exam?

No. It is proctored and delivered through Pearson VUE. Use this for final revision before exam day only.

DP-700 Cheat Sheet: Fabric, Lakehouse, Spark & KQL

A final-revision summary for DP-700. Study aid only - no notes in the proctored exam.

The three skills measured (official weights)

#	Skill area	Weight
1	Implement and manage an analytics solution	30–35%
2	Ingest and transform data	30–35%
3	Monitor and optimize an analytics solution	30–35%

The Fabric workflow (left to right)

Ingest (pipelines, Dataflows Gen2, shortcuts, mirroring) → store (Lakehouse / Warehouse / Eventhouse over OneLake) → transform (notebooks/Spark, T-SQL, KQL) → serve (semantic model, Direct Lake) → secure, monitor & optimise.

Implement and manage - workspace, lifecycle, security

Term	Idea
Workspace settings	Configure Spark, domain, OneLake and Dataflows Gen2 settings
Deployment pipeline	Promote content across dev, test and production
Version control	Git integration and database projects for lifecycle management
Access controls	Workspace-level, item-level, and row/column/object/file-level
OneLake security	Security applied at the OneLake data layer, plus sensitivity labels

Ingest and transform - choose the right tool

Term	Idea
Lakehouse vs Warehouse	Files + Delta + Spark (Lakehouse) vs full T-SQL write engine (Warehouse)
Dataflow Gen2 vs notebook vs pipeline	Low-code transform vs code-first Spark vs orchestration/copy
Full vs incremental load	Reload everything vs load only new/changed rows
OneLake shortcut vs mirroring	Point to data without copying vs continuously replicate a source
Batch tools	PySpark, T-SQL and KQL for transformation

Streaming - Real-Time Intelligence

Term	Idea
Eventstream	No-code capture, transform and route of streaming data
Eventhouse / KQL	Storage for high-volume events, queried with Kusto Query Language
Spark structured streaming	Code-first streaming in notebooks
Windowing	Tumbling/hopping time windows over a stream

Monitor and optimize

Term	Idea
Monitor	Track ingestion, transformation and semantic-model refresh; set alerts
Resolve errors	Pipelines, Dataflows Gen2, notebooks, Eventhouse, T-SQL, shortcuts
Optimise tables	Compact and tune Lakehouse Delta tables
Optimise compute	Tune Spark, the warehouse, Eventstreams/Eventhouses and queries

Exam facts at a glance

Item	Value
Duration	100 minutes
Questions	Not published by Microsoft
Passing score	700 / 1000
Format	Proctored; may include interactive items; Pearson VUE
Validity	1 year (free online renewal)

DP-700 vs DP-203 vs PL-300 - pick by your role

DP-700 is the Fabric-era data-engineering cert and the successor to the retired DP-203 (Azure Synapse / Data Factory). PL-300 is the Power BI analyst exam for reports and visuals, not data engineering. DP-700 engineers the data; PL-300 reports on it. Choose by the role on the job postings you are targeting, not by which exam looks easier.

Microsoft Fabric Data Engineer (DP-700) Cheat Sheet