Microsoft Fabric Analytics Engineer (DP-600)

Audience Profile

The primary audience for this course is data professionals with experience in data modeling, extraction, and analytics. DP-600 is designed for data professionals who want to use Microsoft Fabric to create and deploy enterprise-scale data analytics solutions.

Prerequisites

Before attending this course, it is recommended the 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 designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value using Microsoft Power BI. For more information see Power BI Data Analyst.

Outline

Module:  Introduction to end-to-end analytics using Microsoft Fabric

Discover how Microsoft Fabric can meet your enterprise's analytics needs in one platform. Learn about Microsoft Fabric, how it works, and identify how you can use it for your analytics needs.

Lessons

• Explore end-to-end analytics with Microsoft Fabric
• Data teams and Microsoft Fabric
• Enable and use Microsoft Fabric

Exercise

• None

Module:  Administer Microsoft Fabric

Microsoft Fabric is a SaaS solution for end-to-end data analytics. As an administrator, you can configure features and manage access to suit your organization's needs.

Lessons

• Understand the Fabric Architecture
• Understand the Fabric administrator role
• Manage Fabric security
• Govern data in Fabric

Exercise

• None

Module:  Ingest Data with Dataflows Gen2 in Microsoft Fabric

Data ingestion is crucial in analytics. Microsoft Fabric's Data Factory offers Dataflows for visually creating multi-step data ingestion and transformation using Power Query Online.

Lessons

• Understand Dataflows Gen2 in Microsoft Fabric
• Explore Dataflows Gen2 in Microsoft Fabric
• Integrate Dataflows Gen2 and Pipelines in Microsoft Fabric

Exercise

• Create and use a Dataflow Gen2 in Microsoft Fabric

Module:  Ingest data with Spark and Microsoft Fabric notebooks

Discover how to use Apache Spark and Python for data ingestion into a Microsoft Fabric lakehouse. Fabric notebooks provide a scalable and systematic solution.

Lessons

• Connect to data with Spark
• Write data into a lakehouse
• Consider uses for ingested data

Exercise

• Ingest data with Spark and Microsoft Fabric notebooks

Module:  Use Data Factory pipelines in Microsoft Fabric

Microsoft Fabric includes Data Factory capabilities, including the ability to create pipelines that orchestrate data ingestion and transformation tasks.

Lessons

• Understand pipelines
• Use the Copy Data activity
• Use pipeline templates
• Run and monitor pipelines

Exercise

• Ingest data with a pipeline

Module:  Get started with lakehouses in Microsoft Fabric

Lakehouses merge data lake storage flexibility with data warehouse analytics. Microsoft Fabric offers a lakehouse solution for comprehensive analytics on a single SaaS platform.

Lessons

• Explore the Microsoft Fabric lakehouse
• Work with Microsoft Fabric lakehouses
• Explore and transform data in a lakehouse

Exercise

• Create and ingest data with a Microsoft Fabric lakehouse

Module:  Organize a Fabric lakehouse using medallion architecture design

Explore the potential of the medallion architecture design in Microsoft Fabric. Organize and transform your data across Bronze, Silver, and Gold layers of a lakehouse for optimized analytics.

Lessons

• Describe medallion architecture
• Implement a medallion architecture in Fabric
• Query and report on data in your Fabric lakehouse
• Considerations for managing your lakehouse

Exercise

• Organize your Fabric lakehouse using a medallion architecture

Module:  Use Apache Spark in Microsoft Fabric

Apache Spark is a core technology for large-scale data analytics. Microsoft Fabric provides support for Spark clusters, enabling you to analyze and process data in a Lakehouse at scale..

Lessons

• Prepare to use Apache Spark
• Run Spark code
• Work with data in a Spark dataframe
• Work with data using Spark SQL
• Visualize data in a Spark notebook

Exercise

• Analyze data with Apache Spark

Module:  Work with Delta Lake tables in Microsoft Fabric

Tables in a Microsoft Fabric lakehouse are based on the Delta Lake storage format commonly used in Apache Spark. By using the enhanced capabilities of delta tables, you can create advanced analytics solutions.

Lessons

• Understand Delta Lake
• Create delta tables
• Work with delta tables in Spark
• Use delta tables with streaming data

Exercise

• Use delta tables in Apache Spark

Module:  Get started with data warehouses in Microsoft Fabric

Data warehouses are analytical stores built on a relational schema to support SQL queries. Microsoft Fabric enables you to create a relational data warehouse in your workspace and integrate it easily with other elements of your end-to-end analytics solution.

Lessons

• Understand data warehouse fundamentals
• Understand data warehouses in Fabric
• Query and transform data
• Prepare data for analysis and reporting
• Secure and monitor your data warehouse

Exercise

• Analyze data in a data warehouse

Module:  Load data into a Microsoft Fabric data warehouse

Data warehouse in Microsoft Fabric is a comprehensive platform for data and analytics, featuring advanced query processing and full transactional T-SQL capabilities for easy data management and analysis.

Lessons

• Explore data load strategies
• Use data pipelines to load a warehouse
• Load data using T-SQL
• Load and transform data with Dataflow Gen2

Exercise

• Load data into a warehouse in Microsoft Fabric

Module:  Query a data warehouse in Microsoft Fabric

Data warehouse in Microsoft Fabric is a comprehensive platform for data and analytics, featuring advanced query processing and full transactional T-SQL capabilities for easy data management and analysis.

Lessons

• Use the SQL query editor
• Explore the visual query editor
• Use client tools to query a warehouse

Exercise

• Query a data warehouse in Microsoft Fabric

Module:  Monitor a Microsoft Fabric data warehouse

A data warehouse is a vital component of an enterprise analytics solution. It's important to learn how to monitor a data warehouse so you can better understand the activity that occurs in it..

Lessons

• Monitor capacity metrics
• Monitor current activity
• Monitor queries

Exercise

• Monitor a data warehouse in Microsoft Fabric

Module:  Understand scalability in Power BI

Scalable data models enable enterprise-scale analytics in Power BI. Implement data modeling best practices, use large dataset storage format, and practice building a star schema to design analytics solutions that can scale.

Lessons

• Describe the significance of scalable models
• Implement Power BI data modeling best practices
• Configure large datasets

Exercise

• Create a star schema model

Module:  Create Power BI model relationships

Power BI model relationships form the basis of a tabular model. Define Power BI model relationships, set up relationships, recognize DAX relationship functions, and describe relationship evaluation.

Lessons

• Understand model relationships
• Set up relationships
• Use DAX relationship functions
• Understand relationship evaluation

Exercise

• Work with model relationships

Module:  Use tools to optimize Power BI performance

Use tools to develop, manage, and optimize Power BI data model and DAX query performance.

Lessons

• Use Performance analyzer
• Optimize a data model by using Best Practice Analyzer
• Troubleshoot DAX performance by using DAX Studio

Exercise

• Use tools to optimize Power BI performance

Module:  Enforce Power BI model security

Enforce model security in Power BI using row-level security and object-level security.

Lessons

• Restrict access to Power BI model data
• Restrict access to Power BI model objects
• Apply good modeling practices

Exercise

• Enforce model security