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

DP-500T00 Course

The 4-days instructor-led DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI course enable learners to design and implement enterprise-scale analytics solutions using Microsoft Azure and Microsoft Power BI. With hands-on training and expert instructors, you'll gain the skills and knowledge needed to make data-driven decisions and transform your business. Whether you're a data analyst or an IT professional, this course will equip you with the tools to succeed in today's data-driven world. 

Unlock the power of data and take your analytics skills to the next level! Enroll now and leverage aforementioned services:

  • Post Training Assistance. 
  • Highly Experienced Trainers. 
  • Course Completion Badge.
  • Exclusive Access to Practical Labs.
  • Regular Mock Tests.


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               521 Participants

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Certificate of Attendance from Microsoft

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Microsoft Official Curriculum

Microsoft Partner for Learning Solutions

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

The DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI course is a comprehensive program designed for learners to create understanding of designing and implementing enterprise-scale analytics solutions using Microsoft Azure and Microsoft Power BI.

The course covers various aspects of analytics solutions, including architecture design, data processing, data analysis and visualization, and more. Participants will learn to use Azure services for data storage, processing, and management, as well as how to design and implement data models in Power BI.

The training involves hands-on exercises and real-world scenarios, enabling learners to gain practical experience in designing and implementing analytics solutions. The course is ideal for data analysts, BI professionals, and IT professionals who want to gain expertise in designing and implementing analytics solutions using Microsoft technologies.

By the end of the course, participants will be equipped with the knowledge and skills to design and implement enterprise-scale analytics solutions using Microsoft Azure and Microsoft Power BI, enabling them to make data-driven decisions and transform their organizations.

Course Curriculum

Target Audience

  • To enroll in this course, candidates are required to have a thorough understanding of designing, developing, and implementing enterprise-scale data analytics solutions. They should have advanced knowledge of Power BI, including managing data processing on-premises and in the cloud, utilizing Power Query and Data Analysis Expressions (DAX), and managing data repositories.
  • Additionally, proficiency in consuming data from Azure Synapse Analytics, querying relational databases, analyzing data using Transact-SQL (T-SQL), and visualizing data is essential.

Course Objectives

Upon completing the course, learners will: 

  • Design and implement enterprise-scale data analytics solutions
  • Implement data processing solutions using Azure and on-premises data stores
  • Perform data analysis and manipulation using Power Query and DAX
  • Use Microsoft Power BI to create reports and dashboards for visualizing data insights
  • Implement advanced analytics solutions using Azure Synapse Analytics
  • Design and implement a data management strategy for maintaining data quality and integrity
  • Ensure data security and compliance with regulatory requirements in analytics solutions
  • Optimize performance and cost of analytics solutions using Azure services and features
  • Troubleshoot and resolve common issues in analytics solutions using Azure and Power BI.


  • To enroll in this course, you must have a foundational knowledge of core data concepts and their implementation using Azure data services.
  • Moreover, it is recommended to possess expertise in creating and developing expandable data models, refining and converting data, and empowering advanced analytical capabilities that supply valuable business insights by utilizing Microsoft Power.

About Related Certification: (Microsoft Certified Azure Enterprise Data Analyst Associate)

The Microsoft Certified Azure Data Analyst Associate certification validates the skills and knowledge required to design and implement big data analytics solutions using Microsoft Azure. As an Azure Data Analyst Associate, one can demonstrate their ability to implement Azure data solutions for batch and real-time processing, as well as monitor and optimize data solutions. This certification also validates skills in integrating Azure data storage solutions, ingesting streaming and non-streaming data, and transforming and analyzing data. With this certification, professionals can showcase their expertise in building and managing data pipelines, creating data visualizations, and performing advanced analytics using Azure services such as Azure Synapse Analytics, Azure Stream Analytics, and Power BI.

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Training Options


Instructor led Online Training

  • 4 days Instructor-led Online Training
  • Experienced Subject Matter Experts
  • Approved and Quality Ensured training Material
  • 24*7 leaner assistance and support


Customized to your team's need

  • Blended Learning Delivery Model (Self-Paced E-Learning And/Or Instructor-Led Options)
  • Course, Category, And All-Access Pricing
  • Enterprise-Class Learning Management System (LMS)
  • Enhanced Reporting For Individuals And Teams
  • 24x7 Teaching Assistance And Support

Course Outline

  • Describe the Azure data ecosystem for analytics
  • Describe types of data analytics
  • Understand the data analytics process
  • Explore data job roles in analytics
  • Understand tools for scaling analytics solutions
  • Evaluate whether Microsoft Purview is appropriate for data discovery and governance needs
  • Describe how the features of Microsoft Purview work to provide data discovery and governance
  • Browse, search, and manage data catalog assets
  • Use data catalog assets with Power BI
  • Use Microsoft Purview in Azure Synapse Studio
  • Describe asset classification in Microsoft Purview
  • Register and scan a Power BI tenant
  • Use the search and browse functions to find data assets
  • Describe the schema details and data lineage tracing of Power BI data assets
  • Catalog Azure Synapse Analytics database assets in Microsoft Purview
  • Configure Microsoft Purview integration in Azure Synapse Analytics
  • Search the Microsoft Purview catalog from Synapse Studio
  • Track data lineage in Azure Synapse Analytics pipelines activities
  • Labs: Integrate Azure Synapse Analytics and Microsoft Purview
  • Identify the business problems that Azure Synapse Analytics addresses
  • Describe core capabilities of Azure Synapse Analytics
  • Determine when to use Azure Synapse Analytics
  • Labs: Explore Azure Synapse Analytics
  • Identify capabilities and use cases for serverless SQL pools in Azure Synapse Analytics
  • Query CSV, JSON, and Parquet files using a serverless SQL pool
  • Create external database objects in a serverless SQL pool
  • Labs: Query files using a serverless SQL pool
  • Identify core features and capabilities of Apache Spark
  • Configure a Spark pool in Azure Synapse Analytics
  • Run code to load, analyze, and visualize data in a Spark notebook
  • Labs: Analyze data with Spark
  • Design a schema for a relational data warehouse
  • Create fact, dimension, and staging tables
  • Use SQL to load data into data warehouse tables
  • Use SQL to query relational data warehouse tables
  • Labs: Explore a data warehouse
  • Describe Power BI model fundamentals
  • Determine when to develop an import model
  • Determine when to develop a DirectQuery model
  • Determine when to develop a composite model
  • Choose an appropriate Power BI model framework
  • Describe the importance of building scalable data models
  • Implement Power BI data modeling best practices
  • Use the Power BI large dataset storage format
  • Labs: Create a star schema model
  • Describe Power BI dataflows and use cases
  • Describe best practices for implementing Power BI dataflows
  • Create and consume Power BI dataflows
  • Labs: Create a dataflow
  • Understand how model relationships work
  • Set up relationships
  • Use DAX relationship functions
  • Understand relationship evaluation
  • Labs: Work with model relationships
  • Define time intelligence
  • Use common DAX time intelligence functions
  • Create useful intelligence calculations
  • Explore how calculation groups work
  • Maintain calculation groups in a model
  • Use calculation groups in a Power BI report
  • Labs: Create calculation groups
  • Restrict access to Power BI model data with RLS
  • Restrict access to Power BI model objects with OLS
  • Apply good development practices to enforce Power BI model security
  • Labs: Enforce model security
  • Optimize queries using a performance analyzer
  • Troubleshoot DAX performance using DAX Studio
  • Optimize a data model using Tabular Editor
  • Labs: Use tools to optimize Power BI performance
  • Create and import a custom report theme
  • Create custom visuals with R or Python
  • Enable personalized visuals in a report
  • Review report performance using Performance Analyzer
  • Design and configure Power BI reports for accessibility
  • Describe Power BI real-time analytics
  • Set up automatic page refresh
  • Create real-time dashboards
  • Set up auto-refresh paginated reports
  • Get data
  • Create a paginated report
  • Work with charts and tables on the report
  • Publish the report
  • Define the key components of an effective BI governance model
  • Describe the key elements associated with data governance
  • Configure, deploy, and manage elements of a BI governance strategy
  • Set up BI help and support settings
  • Understand the differences between My workspace, workspaces, and apps
  • Describe new workspace capabilities and how they improve the user experience
  • Anticipate migration impact on Power BI users
  • Share, publish to the web, embed links, and secure Power BI reports dashboards, and content
  • Discover what usage metrics are available through the Power BI admin portal
  • Optimize the use of usage metrics for dashboards and reports
  • Distinguish between audit logs and the activity logs
  • Describe the difference between Power BI Pro and Power BI Premium
  • Define dataset eviction
  • Explain how Power BI manages memory resources
  • List three external tools you can use with Power BI Premium
  • Understand the difference between gateways, the various connectivity modes, and data refresh methods
  • Describe the gateway network requirements, where to place the gateway in your network, and how to use clustering to ensure high availability
  • Scale, monitor, and manage gateway performance and users
  • Describe the various embedding scenarios that allow you to broaden the reach of Power BI
  • Understand the options for developers to customize Power BI solutions
  • Learn to provision and optimize Power BI embedded capacity and create and deploy dataflows
  • Build custom Power BI solutions template apps
  • Use REST APIs to automate common Power BI admin tasks
  • Apply Power BI Cmdlets for Windows PowerShell and PowerShell core
  • Use Power BI Cmdlets
  • Automate common Power BI admin tasks with scripting
  • Describe the Power BI and Synapse workspace integration
  • Understand Power BI data sources
  • Describe optimization options
  • Visualize data with serverless SQL pools
  • Labs: Create a new data source to use in Power BI
  • Labs: Create a new Power BI report in Synapse Studio
  • Labs: Connect to Power BI from Synapse
  • Labs: Improve performance with materialized views and result-set caching
  • Outline the application lifecycle process
  • Choose a source control strategy
  • Design a deployment strategy
  • Articulate the benefits of deployment pipelines
  • Create a deployment pipeline using Premium workspaces
  • Assign and deploy content to pipeline stages
  • Describe the purpose of deployment rules
  • Deploy content from one pipeline stage to another
  • Create specialized datasets
  • Create live and DirectQuery connections
  • Use Power BI service lineage view
  • Use XMLA endpoint to connect datasets
  • Labs: Create reusable Power BI assets

Course Reviews


DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI is a training course that covers the design and implementation of analytics solutions using Microsoft Azure and Power BI.

This course is intended for data professionals, data architects, and business intelligence professionals.

The prerequisites for this course include a basic understanding of data warehouse schema topology, SQL Server, and Power BI.

The main topics covered in this course include data platform architecture, data modeling, data transformation, data loading, and Azure Analysis Services.

The benefits of taking DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI course include gaining the knowledge and skills needed to design and implement enterprise-scale analytics solutions using Microsoft Azure and Power BI.

Job opportunities after completing this course may include roles such as data analyst, data engineer, and business intelligence analyst.

The duration of course is 4-days.

Vinsys is a reliable training partner with a track record of providing top-notch IT training. Our certified and experienced instructors are dedicated to ensuring that learners comprehend the course material thoroughly. The training is comprehensive and covers all aspects of the subject matter.