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Data Science and AI
Microsoft Fabric Data Engineer
Ingest, transform and optimise data in Microsoft Fabric (Exam DP-700)
A lab-based classroom course in data engineering on Microsoft Fabric. It follows the three skill areas of the DP-700 study guide: implement and manage an analytics solution, ingest and transform data, and monitor and optimise an analytics solution. The exam expects SQL, PySpark and KQL.
10Modules
IntermediateLevel
3 monthsDuration
COURSE THUMBNAIL
What you will be able to do
Configure and secure a Fabric analytics workspace
Orchestrate data loads with pipelines and notebooks
Ingest and transform batch data with PySpark, SQL and KQL
Process streaming data
Monitor, troubleshoot and optimise an analytics solution
Sit Exam DP-700 having covered every skill area Microsoft lists
Course outline
01
Fabric workspaces and OneLake settings
02
Lifecycle management: version control and deployment pipelines
03
Security and governance: access controls, masking and sensitivity labels
04
Orchestration with pipelines and notebooks
05
Loading patterns: full, incremental and streaming
06
Ingesting and transforming batch data with PySpark, SQL and KQL
07
Ingesting and transforming streaming data
08
Monitoring Fabric items and configuring alerts
09
Identifying and resolving errors
10
Optimizing lakehouses, warehouses, Spark and queries; exam practice
Tools you will use
Microsoft FabricOneLakePySparkSQLKQLFabric pipelinesFabric notebooks
What you need
Working knowledge of SQL
Basic programming in Python
