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

  • Length 4 days
  • Version A
Course overview
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Why study this course

This four-day 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 visualise data. In this course, students will use Microsoft Purview, Azure Synapse Analytics, and Power BI to build analytics solutions.

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What you’ll learn

  • Implement and manage a data analytics environment

  • Query and transform data

  • Implement and manage data models

  • Explore and visualise data

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Who is the course for?

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, analysing data by using Transact-SQL (T-SQL), and visualising data.

Course subjects

Module 1: Introduction to data analytics on Azure
This module explores key concepts of data analytics, including types of analytics, data, and storage. Students will explore the analytics process and tools used to discover insights and learn about the responsibilities of an enterprise data analyst and what tools are available to build scalable solutions.


  • Explore Azure data services for modern analytics

  • Understand concepts of data analytics

  • Explore data analytics at scale

Module 2: Govern data across an enterprise
This module explores the role of an enterprise data analyst in organisational data governance. Students will explore the use of Microsoft Purview to register and catalog data assets, to discover trusted assets for reporting, and to scan a Power BI environment.


  • 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
This module explores the use of Azure Synapse Analytics for exploratory data analysis. Students will explore the capabilities of Azure Synapse Analytics including the basics of data warehouse design, querying data using T-SQL, and exploring data using Spark notebooks.


  • Introduction to Azure Synapse Analytics

  • Use Azure Synapse serverless SQL pool to query files in a data lake

  • Analyse data with Apache Spark in Azure Synapse Analytics

  • Analyse data in a relational data warehouse

Lab : Query data in Azure
Lab : Create a star schema model
Lab : Explore data in Spark notebooks

Module 4: Prepare data for tabular models in Power BI
This module explores the fundamental elements of preparing data for scalable analytics solutions using Power BI. Students will explore model frameworks, considerations for building data models that will scale, Power Query optimisation techniques, and the implementation of Power BI dataflows.


  • Choose a Power BI model framework

  • Understand scalability in Power BI

  • Optimise Power Query for scalable solutions

  • Create and manage scalable Power BI dataflows

Lab : Create a dataflow

Module 5: Design and build scalable tabular models
This module explores the critical underlying aspects of tabular modeling for building Power BI models that can scale. Students will learn about model relationships and model security, working with direct query, and using calculation groups.


  • Create Power BI model relationships

  • Enforce model security

  • Implement DirectQuery

  • Create calculation groups

  • Use tools to optimise Power BI performance

Lab : Create model relationships
Lab : Design and build tabular models
Lab : Create calculation groups
Lab : Use tools to optimise Power BI performance
Lab : Enforce model security

Module 6: Implement advanced data visualisation techniques by using Power BI
This module explores data visualisation concepts including accessibility, customisation of core data models, real-time data visualisation, and paginated reporting.


  • Understand advanced data visualisation concepts

  • Customise core data models

  • Monitor data in real-time with Power BI

  • Create and distribute paginated reports in Power BI report builder

Lab : Create and distribute paginated reports in Power BI Report Builder
Lab : Monitor data in real-time with Power BI

Module 7: Implement and manage an analytics environment
This module explores key considerations for implementing and managing Power BI. Students will understand key recommendations for administration and monitoring of Power BI, including configuration and management of Power BI capacity.


  • Provide governance in a Power BI environment

  • Facilitate collaboration and sharing in Power BI

  • Monitor and audit usage

  • Provision Premium capacity in Power BI

  • Establish a data access infrastructure in Power BI

  • Broaden the reach of Power BI

  • Automate Power BI administration

  • Build reports using Power BI within Azure Synapse Analytics

Module 8: Manage the analytics development lifecycle
This module explores considerations for deployment, source control, and application lifecycle management of analytics solutions. Students will understand what to recommend and will be able to deploy and manage automated and reusable Power BI assets.


  • Design a Power BI application lifecycle management strategy

  • Create and manage a Power BI deployment pipeline

  • Create and manage Power BI assets

Lab : Create reusable Power BI assets

Module 9: Integrate an analytics platform into an existing IT infrastructure
This module explores the integration of a Power BI analytics solution into existing Azure infrastructure. Students will understand Power BI tenant and workspace configurations, along with considerations for Power BI deployment in an organisation.


  • 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


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

  • A foundational knowledge of core data concepts and how they’re implemented 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. For more information see Power BI Data Analyst.

Terms & Conditions

The supply of this course by DDLS is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.

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Microsoft Azure Data Offers
Book & sit any of the below Microsoft Azure Data courses before Friday, 14th April 2023, to receive a 10% discount and a complimentary exam voucher upon request.