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Exam Prep DP-700: Microsoft Fabric Data Engineer Associate Specialization

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Exam Prep DP-700: Microsoft Fabric Data Engineer Associate Specialization

Become Microsoft Certified Fabric Data Engineer. Hands-On Preparation for the DP-700: Microsoft Fabric Data Engineer Associate Certification

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Instructor: Whizlabs Instructor

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Get in-depth knowledge of a subject
Intermediate level

Recommended experience

2 months to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

2 months to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Design and implement scalable batch and streaming ingestion pipelines

  • Transform, model, and prepare data using Spark, SQL, KQL, and Dataflows

    Secure, govern, and manage Fabric workspaces and analytics environments

  • Monitor, optimize, and troubleshoot performance across Fabric workloads

  • Build end-to-end analytics solutions aligned to DP-700 certification skills

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Taught in English
Recently updated!

November 2025

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Specialization - 3 course series

What you'll learn

  • Understand the core architecture, purpose, and components of the Microsoft Fabric platform.

  • Identify key elements of the Fabric ecosystem, including licensing models, portals, and core services.

  • Perform impact analysis, manage database projects, and plan deployment solutions for analytics lifecycle governance.

  • Schedule, monitor, and optimize dataflows and notebooks to maintain secure and reliable analytics operations.

Skills you'll gain

Category: Application Deployment
Category: Apache Spark
Category: Data Security
Category: Exploratory Data Analysis
Category: Analytics
Category: Version Control
Category: Data Lakes
Category: Power BI
Category: Governance
Category: Data Pipelines
Category: Microsoft Power Platform
Category: SQL
Category: Advanced Analytics
Category: Data Management
Category: Data Analysis Expressions (DAX)
Category: Data Governance
Category: CI/CD
Category: Azure Synapse Analytics
Category: Microsoft Excel
Category: Microsoft Azure

What you'll learn

  • Design and implement performant batch and incremental data loading patterns in Microsoft Fabric.

  • Ingest and process real-time streaming data using KQL, Eventstreams, and Spark Structured Streaming.

  • Apply data transformation and quality techniques such as windowing, aggregation, deduplication, and denormalization.

  • Deploy scalable, analytics-ready datasets for reporting, dashboards, and downstream insight generation.

Skills you'll gain

Category: Data Pipelines
Category: Data Transformation
Category: Extract, Transform, Load
Category: Data Lakes
Category: PySpark
Category: Data Processing
Category: Data Integration
Category: Analytics
Category: Apache Spark
Category: Real Time Data
Category: Data Quality
Category: Data Governance
Category: Power BI

What you'll learn

  • Monitor and troubleshoot data ingestion, transformation, and semantic models using Microsoft Fabric monitoring tools, alerts, and diagnostic views.

  • Optimize performance for pipelines, notebooks, SQL endpoints, Eventstreams, Spark workloads, semantic models across Fabric’s analytics engine.

  • Identify, analyze, and resolve Fabric errors including T-SQL, Eventhouse, pipeline, and Dataflow errors using built-in debugging capabilities.

  • Operationalize and govern analytics solutions through proactive monitoring, alerting, and continuous performance improvement.

Skills you'll gain

Category: Data Pipelines
Category: System Monitoring
Category: Performance Tuning
Category: Debugging
Category: Data Warehousing
Category: Apache Spark
Category: Data Lakes
Category: Data Analysis Expressions (DAX)
Category: Transact-SQL
Category: Analytics
Category: Data Transformation
Category: SQL Server Integration Services (SSIS)
Category: Star Schema
Category: Real Time Data
Category: Power BI
Category: Microsoft Azure
Category: PySpark
Category: Data Modeling
Category: Azure Synapse Analytics

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Instructor

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135 Courses93,935 learners

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