DP-700: Implement Data Engineering Solutions using Microsoft Fabric
MOC: DP-700T00
MS Subscription
Interface Gold
This course covers methods and practices to implement data engineering solutions by using Microsoft Fabric. Students will learn how to design and develop effective data loading patterns, data architectures, and orchestration processes. Objectives for this course include ingesting and transforming data and securing, managing, and monitoring data engineering solutions. This course is designed for data professionals with some data integration and orchestration experience.
What you will learn
With a focus on practical applications, the course covers:
- Big data
- Data analytics
- Data engineering
- Data integration
- Data management
What products and services will you use and learn about in this course
- OneLake
- Data Factory
- Dataflows Gen2
- Lakehouse
- Data Warehouse
- Real-Time Intelligence (Real-time Analytics )
- KQL Database & Kusto Query Language (KQL
- Notebooks
- Activator
- PySpark (Python)
- T-SQL (Transact-SQL)
- KQL
Prepare for the Microsoft Certified: Fabric Data Engineer Associate Certification
This course is designed to help students confidently prepare for the DP-700: Microsoft Certified: Fabric Data Engineer Associate exam.
Note: To pass the certification test, studying outside the course may be required to ensure all the concepts are fully understood.
- $2,595
- 4 Days, Labs, Live Q&A
- Replay™ Class Recordings Included
- Included in “all-you-can-eat” Microsoft Live Training Subscription
Course Outline
Learning Path: Explore end-to-end analytics with Microsoft Fabric
Modules:
- Introduction
- Get started with lakehouses in Microsoft Fabric
- Use Apache Spark in Microsoft Fabric
- Work with Delta Lake tables in Microsoft Fabric
- Ingest data with Dataflows (Gen2) in Microsoft Fabric
Exercise:
- Create and ingest data with a Microsoft Fabric lakehouse
- Analyze data with Apache Spark
- Use delta tables in Apache Spark
- Create and use a Dataflow Gen2 in Microsoft Fabric
Learning Path: Orchestrate processes and data movement
Modules:
- Organize a Fabric lakehouse using medallion architecture design
- Get started with Real-Time Intelligence in Microsoft Fabric
- Use real time eventstreams in Microsoft Fabric
- Work with real-time data in a Microsoft Fabric eventhouse
Exercises
- Ingest data with a pipeline
- Organize your Fabric lakehouse using a medallion architecture
- Get started with Real-Time Intelligence in Microsoft Fabric
- Ingest real-time data with Eventstreams in Microsoft Fabric
- Work with data in a Microsoft Fabric eventhouse
Learning Path: Create Real-Time Dashboards Use Activator
Modules:
- Get started with data warehouses in Microsoft Fabric
- Load data into a Microsoft Fabric data warehouse
- Fabric SQL DB
- Monitor a Microsoft Fabric data warehouse
- Secure a Microsoft Fabric data warehouse
- Tools for Fabric – VS Code
Exercises:
- Get started with Analyzing in data warehouse
- Load data into a Microsoft Fabric data warehouse
- Work with SQL Database in Microsoft Fabric
- Monitor a data warehouse in Microsoft Fabric
Learning Path: Implement continuous integration/continuous delivery (CI/CD)
Modules:
- Introduction
- Monitor activities in Microsoft
- One Lake security
- Secure data access in Microsoft Fabric
- Administer Microsoft Fabric
Exercises:
- Implement deployment pipelines in Microsoft Fabric
- Use Activator in Fabric
- Monitor Fabric activity in the Monitor hub
- Secure data access in Microsoft Fabric
Audience
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).
Prerequisites
Before attending this course, students must have:
- A foundational knowledge of core data concepts
- How they’re implemented using Microsoft data services
- Experience with data extraction, transformation, loading, and orchestration