Course Code: 19273

DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI

Class Dates:
4 Days
Class Time:
Instructor-Led Training, Virtual Instructor-Led Training


  • Course Overview
  • This course covers methods and practices for performing advanced data analytics at scale. Students will build on existing analytics experience and will learn to implement and manage a data analytics environment, query and transform data, implement and manage data models, and explore and visualize data. In this course, students will use Microsoft Purview, Azure Synapse Analytics, and Power BI to build analytics solutions.

    Skills gained
    Implement and manage a data analytics environment
    Query and transform data
    Implement and manage data models
    Explore and visualize data
  • Audience
  • Candidates for this course should have subject matter expertise in designing, creating, and deploying enterprise-scale data analytics solutions. Specifically, candidates should have advanced Power BI skills, including managing data repositories and data processing in the cloud and on-premises, along with using Power Query and Data Analysis Expressions (DAX). They should also be proficient in consuming data from Azure Synapse Analytics and should have experience querying relational databases, analyzing data by using Transact-SQL (T-SQL), and visualizing data.


  • Before attending this course, it is recommended that students have:

    A foundational knowledge of core data concepts and how they’re impl

    emented using Azure 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.


Course Details

  • Module 1: Introduction to data analytics on Azure
  • Explore Azure data services for modern analytics
  • Understand concepts of data analytics
  • Explore data analytics at scale
  • Module 2: Govern data across an enterprise
  • Introduction to Microsoft Purview
  • Discover trusted data using Microsoft Purview
  • Catalog data artifacts by using Microsoft Purview
  • Manage Power BI artifacts by using Microsoft Purview
  • Module 3: Model, query, and explore data in Azure Synapse
  • Introduction to Azure Synapse Analytics
  • Implement star schema design and query relational data in Azure
  • Analyze data with a serverless SQL pool in Azure Synapse Analytics
  • Optimize data warehouse query design
  • Analyze data with a Spark Pool in Azure Synapse Analytics
  • Lab : Query data in Azure
  • Lab : Explore data in Spark notebooks
  • Lab : Create a star schema model
  • Module 4: Prepare data for tabular models in Power BI
  • Choose a Power BI model framework
  • Understand scalability in Power BI
  • Optimize Power Query for scalable solutions
  • Create and manage scalable Power BI dataflows
  • Lab : Create a dataflow
  • Module 5: Design and build scalable tabular models
  • Create Power BI model relationships
  • Enforce model security
  • Implement DirectQuery
  • Create calculation groups
  • Lab : Create model relationships
  • Lab : Enforce model security
  • Lab : Design and build tabular models
  • Lab : Create calculation groups
  • Module 6: Optimize enterprise-scale tabular models
  • Optimize performance using Synapse and Power BI
  • Improve query performance with hybrid tables, dual storage mode, and aggregations
  • Use tools to optimize Power BI performance
  • Lab : Use tools to optimize Power BI performance
  • Lab : Improve query performance using aggregations
  • Lab : Improve query performance with dual storage mode
  • Lab : Improve performance with hybrid tables
  • Module 7: Implement advanced data visualization techniques by using Power BI
  • Understand advanced data visualization concepts
  • Customize core data models
  • Monitor data in real-time with Power BI
  • Create and distribute paginated reports in Power BI report builder
  • Lab : Monitor data in real-time with Power BI
  • Lab : Create and distribute paginated reports in Power BI Report Builder
  • Module 8: Implement and manage an analytics environment
  • Recommend Power BI administration settings
  • Recommend a monitoring and auditing solution for a data analytics environment
  • Configure and manage Power BI capacity
  • Establish a data access infrastructure in Power BI
  • Module 9: Manage the analytics development lifecycle
  • Recommend a deployment strategy for Power BI assets
  • Recommend a source control strategy for Power BI assets
  • Perform impact analysis of downstream dependencies from dataflows and datasets
  • Recommend automation solutions for the analytics development lifecycle, including Power BI REST API
  • Deploy and manage datasets by using the XMLA endpoint
  • Deploy reusable assets
  • Lab : Create reusable Power BI assets
  • Module 10: Integrate an analytics platform into an existing IT infrastructure
  • Recommend and configure a Power BI tenant or workspace
  • Identify requirements for a solution, including features, performance, and licensing strategy
  • Integrate an existing Power BI workspace into Azure Synapse Analytics