MIcrosoft Fabric Data Engineer (DP-700T00)

About this Course

This course is for data professionals with experience in data extraction, transformation, and loading. Students will learn how to design and develop effective data loading patterns, data architectures, and orchestration processes.

Audience Profile

This audience for this course is data professionals with experience in data extraction, transformation, and loading. DP-700 is designed for professionals who need to create and deploy data engineering solutions using Microsoft Fabric for enterprise-scale data analytics. Learners should also have experience at manipulating and transforming data with one of the following programming languages: Structured Query Language (SQL), PySpark, or Kusto Query Language (KQL).

Outline

Learning Path 1: Ingest data with Microsoft Fabric

Explore how Microsoft Fabric enables you to ingest and orchestrate data from various sources (such as files, databases, or web services) through dataflows, notebooks, and pipelines.

Learning Path 2: Implement a Lakehouse with Microsoft Fabric

This learning path introduces the foundational components of implementing a data lakehouse with Microsoft Fabric.

Learning Path 3: Implement Real-Time Intelligence with Microsoft Fabric

Learning Path 4: Implement a data warehouse with Microsoft Fabric

Explore the data warehousing process and learn how to load, monitor, secure, and query a warehouse in Microsoft Fabric.

Learning Path 5: Manage a Microsoft Fabric environment

Microsoft Fabric is a Software-as-a-Service platform for data analytics. Learn how to manage your environment through Continuous Integration/Continuous Deployment (CI/CD), monitoring, and security.

Prerequisites

While there are no required prerequisites for taking this course, it is recommended that students have:

• A foundational knowledge of core data concepts and how they’re implemented using Microsoft data services. For more information see Azure Data Fundamentals.
• Experience with data extraction, transformation, loading, and orchestration, such as skills in the DP-203: Azure Data Engineer certification.
• Should also have experience at manipulating and transforming data with one of the following programming languages: Structured Query Language (SQL), PySpark, or Kusto Query Language (KQL).