DP-600: Microsoft Fabric Analytics Engineer

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  • 4 Days
  • Private Group Training
01

Course Overview

This Microsoft Fabric Analytics Engineer training teaches attendees the methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students learn how to use Microsoft Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models, to create and deploy analytics assets.

02

Key Learning Areas

  • Describe end-to-end analytics in Microsoft Fabric
  • Describe Fabric admin tasks
  • Navigate the admin center
  • Manage user access
  • Describe Dataflow capabilities in Microsoft Fabric
  • Create Dataflow solutions to ingest and transform data
  • Include a Dataflow in a pipeline
  • Ingest external data to Fabric lakehouses using Spark
  • Configure external source authentication and optimization
  • Load data into lakehouse as files or as Delta tables
  • Describe pipeline capabilities in Microsoft Fabric
  • Use the Copy Data activity in a pipeline
  • Create pipelines based on predefined templates
  • Run and monitor pipelines
  • Describe core features and capabilities of lakehouses in Microsoft Fabric
  • Create a lakehouse
  • Ingest data into files and tables in a lakehouse
  • Query lakehouse tables with SQL
  • Describe the principles of using the medallion architecture in data management
  • Apply the medallion architecture framework within the Microsoft Fabric environment
  • Analyze data stored in the lakehouse using DirectLake in Power BI
  • Describe best practices for ensuring the security and governance of data stored in the medallion architecture
  • Configure Spark in a Microsoft Fabric workspace
  • Identify suitable scenarios for Spark notebooks and Spark jobs
  • Use Spark dataframes to analyze and transform data
  • Use Spark SQL to query data in tables and views
  • Visualize data in a Spark notebook
  • Understand Delta Lake and delta tables in Microsoft Fabric
  • Create and manage delta tables using Spark
  • Use Spark to query and transform data in delta tables
  • Use delta tables with Spark structured streaming
  • Learn different strategies to load data into a data warehouse in Microsoft Fabric
  • Learn how to build a data pipeline to load a warehouse in Microsoft Fabric
  • Learn how to load data in a warehouse using T-SQL
  • Learn how to load and transform data with dataflow (Gen 2)
  • Use SQL query editor to query a data warehouse.
  • Explore how visual query editor works.
  • Learn how to connect and query a data warehouse using SQL Server Management Studio
  • Monitor capacity unit usage with the Microsoft Fabric Capacity Metrics app
  • Monitor current activity in the data warehouse with dynamic management views
  • Monitor querying trends with query insights views
  • Describe the importance of building scalable data models
  • Implement Power BI data modeling best practices
  • Use the Power BI large dataset storage format
  • Understand how model relationships work
  • Set up relationships
  • Use DAX relationship functions
  • Understand relationship evaluation
  • Optimize queries using a performance analyzer
  • Troubleshoot DAX performance using DAX Studio
  • Optimize a data model using Tabular Editor
03

Course Outline

Introduction to End-to-End Analytics using Microsoft Fabric

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

Administer Microsoft Fabric

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

Ingest Data with Dataflows Gen2 in Microsoft Fabric

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

Ingest Data with Spark and Microsoft Fabric Notebooks

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

Use Data Factory Pipelines in Microsoft Fabric

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

Get Started with Lakehouses in Microsoft Fabric

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

Organize a Fabric lakehouse using Medallion Architecture Design

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

Use Apache Spark in Microsoft Fabric

  • 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

Work with Delta Lake Tables in Microsoft Fabric

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

Get Started with Data Warehouses in Microsoft Fabric

  • 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

Load Data into a Microsoft Fabric Data Warehouse

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

Query a Data Warehouse in Microsoft Fabric

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

Monitor a Microsoft Fabric Data Warehouse

  • Monitor capacity metrics
  • Monitor current activity
  • Monitor queries

Understand Scalability in Power BI

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

Create Power BI Model Relationships

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

Use Tools to Optimize Power BI Performance

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

Enforce Power BI Model Security

  • Restrict access to Power BI model data
  • Restrict access to Power BI model objects
  • Apply good modeling practices
04

Who Benefits

  • New or aspiring data engineers. This course covers literally every skill and Microsoft tool a new data engineer needs to know to get started with creating analytics solutions using Fabric. If you’re just getting started in the career field, this course and the Analytics Engineer Associate cert are clear representations of your abilities and familiarity with data analytics solutions.
  • Experienced data engineers. If you’ve already been working as a data engineer for several years, this course is a great way to solidify your familiarity with the Microsoft Fabric platform specifically and get up to speed with industry best practices. Earn the Analytics Engineer Associate certification and you’ll have a solid foundation underneath you that can take you to better paying jobs in data.
05

Prerequisites

  • Attendees should have achieved PL-300: Power BI Data Analyst Associate or have similar experience using Power BI for data transformation, modeling, visualization, and sharing. Also, learners should have experience building and deploying data analytics solutions at the enterprise level.
  • Attendees should have completed DP-900: Azure Data Fundamentals or demonstrate equivalent experience.
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