Search Results

Further Information

• DP-600: Course Overview

  This course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will learn how to use Fabric dataflows, pipelines, and notebooks to develop analytics assets such as semantic models, data warehouses, and lakehouses.  This course is designed for experienced data professionals skilled at data preparation, modeling, analysis, and visualisation, such as the PL-300: Power BI Data Analyst certification.

  The primary audience for this course is data professionals with experience in data modeling and analytics. DP-600 is designed for professionals who want to use Microsoft Fabric to create and deploy enterprise-scale data analytics solutions. Learners should have prior experience with one of the following programming languages: Structured Query Language (SQL), Kusto Query Language (KQL), or Data Analysis Expressions (DAX).

• DP-600: Course Modules

  Module 1: Get started with Microsoft Fabric

  Module 2: Implement a data warehouse with Microsoft Fabric

  Module 3: Work with semantic models in Microsoft Fabric

  Module 4: Administer and govern Microsoft Fabric

• DP-600: Course Objectives

  By the end of the course, you should be able to:

  • Explore how to implement data analytics solutions on a single platform with Microsoft Fabric. Integrate, transform, and store data to train AI models and create insightful reports.
  • Explore the data warehousing process and learn how to load, monitor, secure, and query a warehouse in Microsoft Fabric.
  • Designing reports for enterprise scale requires more than just connecting to data. Understanding semantic models and strategies for scalability and lifecycle management are key to a successful enterprise implementation. This learning path helps you prepare for the Fabric Analytics Engineer Certification.

   

• DP-600: Prerequisites

  Prerequisites include:

  • You should be familiar with basic data concepts and terminology, including data engineering, modeling, and analysis.
  • You should be familiar with basic data concepts and terminology.
  • Familiarity with Microsoft Fabric
  • Work with semantic models in Microsoft Fabric