DP-700 Tests Microsoft Fabric Engineering — Not the Retired DP-203 Synapse Syllabus
DP-203 and the Azure Data Engineer Associate retired on 31 March 2025. Its successor, DP-700, certifies Fabric Data Engineer Associate: lakehouses, warehouses, eventhouses, OneLake security and capacity-aware optimisation.
Check Your Readiness →Most candidates understand Microsoft Certified: Fabric Data Engineer Associate (DP-700) concepts — and still fail. This exam tests how you apply knowledge under pressure.
Three official domains of equal weight, each split here into its two main skill areas. Questions pair a Fabric item with a requirement such as least-privilege sharing, incremental loads, late-arriving data, small files or slow queries. Expect PySpark, T-SQL and KQL snippets. 100 minutes; question count not published.
Create a OneLake shortcut to the database tables
Shortcuts point at storage such as OneLake, ADLS Gen2 or S3, not operational databases. Mirroring replicates the database into Delta tables in OneLake in near real time and exposes a read-only SQL analytics endpoint.
Run INSERT through the lakehouse SQL analytics endpoint
The lakehouse SQL analytics endpoint is read-only. Write lakehouse tables with Spark notebooks, pipelines or Dataflow Gen2, or land the data in a Fabric Warehouse if T-SQL writes are a hard requirement.
Expect the deployment pipeline to copy the table data
Deployment pipelines promote item definitions and metadata across two to ten stages, with deployment rules swapping data sources per stage. Rows in the target stage must be loaded separately by pipelines, notebooks or dataflows.
Filter out facts whose dimension key is not found
Insert an inferred member: a placeholder dimension row carrying the business key, so the fact loads with a valid surrogate key. When the real customer row arrives, the placeholder's attributes are updated.
Increase the eventhouse retention policy
Retention controls how long data is kept at all. The caching policy controls how much stays in hot cache, which is what speeds queries; extend the hot period to cover the range being queried.
DP-700 is built on Microsoft Fabric: workspaces, lakehouses, warehouses, eventhouses, Dataflow Gen2, notebooks and OneLake shortcuts. Synapse-era topics such as dedicated SQL pool distribution choices are outside the outline, while workspace roles, deployment pipelines and capacity monitoring are in it.
Viewer exposes every item in the workspace, and Contributor can edit items and sees unmasked data. Sharing a single warehouse or lakehouse with item permissions such as Read or ReadData is the least-privilege answer when the scenario names one item.
Masking obscures values in query results; users with UNMASK and administrators still see real data. When a column must be inaccessible, use column-level security, and remember warehouse row-level security does not protect files Spark reads from OneLake with ReadAll.
VACUUM deletes unreferenced files older than the retention threshold, seven days by default, and only saves storage. Slow reads from many small files need OPTIMIZE compaction, with V-Order for read-optimised Parquet and Z-order on frequently filtered columns.
The checkpoint records stream progress, so a restarted query resumes instead of reprocessing data, and exactly-once sinks require it. Pair it with withWatermark to bound late events so state for windowed aggregates can be cleaned up.
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