DP-600 Microsoft Fabric Analytics Engineer

Target group

• Data engineers who want to learn how to design data storage and related ETL processes within the Microsoft Fabric environment.

• Data analysts who will design data models in Microsoft Fabric for subsequent analysis and visualization of stored data in Microsoft Power BI.

• Data and BI architects who want to understand how to design the architecture of a modern data analytics solution built on the Microsoft Fabric platform.

Course structure

Introduction to Data Analytics in Microsoft Fabric

• Get acquainted with the individual services offered by Microsoft Fabric

• Learn which team roles work with which services in Microsoft Fabric

Administration of Microsoft Fabric

• Familiarize yourself with key concepts and components of Microsoft Fabric

• Discover management and security options within this environment

• Understand how compute capacity is allocated

Introduction to Lakehouses in Microsoft Fabric

• Get to know Lakehouse storage and understand how data is stored in Microsoft Fabric

• Understand the difference between Data Lake and Data Warehouse

• Learn the options for loading data into Fabric Lakehouse and subsequent querying

Using Apache Spark in Microsoft Fabric

• Explore the notebook environment for running Apache Spark computations on your data

• Learn how to load data into Spark DataFrames and write it back to Lakehouse

• Try out basic data analysis and visualization in notebooks

Working with Delta Lake Tables

• Understand the principles of the Delta Lake storage format

• Learn to create and manipulate Delta tables in code

• Get familiar with data versioning options in Delta tables

Securing Fabric Lakehouse

• Learn principles of access security for data stored in OneLake

• Understand how to set permissions and share data

Data Loading Using Dataflow Gen2 in Microsoft Fabric

• Understand the principles of Dataflow Gen2

• Learn to create basic Dataflows for data ingestion

• Explore options for building Pipelines to orchestrate data loading and transformation

Using Data Factory Pipelines in Microsoft Fabric

• Understand the basic concepts of Pipelines in Microsoft Fabric

• Discover commonly used activities

• Practice loading data using Data Factory Pipelines

Loading Data with Apache Spark and Notebooks

• Learn to connect to external data sources via notebooks

• Understand efficient ways to store data in Lakehouse and Delta tables

Organizing Lakehouse Using Medallion Architecture

• Learn the principles of medallion architecture and data quality at different layers

• Discover how to implement basic elements of this architecture

• Practice organizing data in Fabric Lakehouse using medallion architecture

Introduction to Data Warehouses in Microsoft Fabric

• Understand main differences between Warehouse and Lakehouse in Microsoft Fabric

• Get familiar with key features of data warehouses in Microsoft Fabric

• Learn fundamental principles of designing data warehouses, including dimension and fact tables

• Learn to define relationships between tables propagated to semantic models

Loading Data into Data Warehouse in Microsoft Fabric

• Understand basic ETL process principles

• Learn options for loading data into dimension and fact tables

• Practice loading data into the data warehouse

Querying Data in Data Warehouse in Microsoft Fabric

• Learn to run queries on the data warehouse using T-SQL

• Discover how to use the Visual Query Editor

• Practice connecting via SQL Server Management Studio

Monitoring Data Warehouse in Microsoft Fabric

• Explore monitoring options for compute capacity using Fabric Capacity Metrics app

• Learn to monitor running queries using Dynamic Management Views

• Discover how to track frequent and resource-intensive queries using Query Insights

Securing Data Warehouse in Microsoft Fabric

• Understand differences in security features within Microsoft Fabric and additional options offered by data warehouses

• Learn to set permissions at the data warehouse object level using T-SQL

Scalability in Power BI

• Understand the importance of designing scalable semantic models in Power BI

• Learn best practices for data modeling in Power BI

• Try using the Power BI large semantic model storage format

Relationships Between Data in the Model

• Learn to create relationships between data in the data model

• Get familiar with DAX functions for working with relationships

• Understand how relationships are evaluated

Using Tools to Optimize Power BI Performance

• Learn to optimize performance using aggregations, dual storage mode, and hybrid tables

• Discover how to optimize queries using the Performance Analyzer tool

• Find out how to tune DAX query performance using DAX Studio and optimize models with Tabular Editor

Enforcing Security in the Semantic Model

• Learn to restrict data access using Object-Level Security and Row-Level Security