DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI
Duration: 4 Days (32 Hours)
The DP-500 course focuses on providing students with advanced methods and practices for performing data analytics at scale. This course is designed for individuals with existing analytics experience and aims to enhance their skills in implementing and managing a data analytics environment.
Throughout the course, students will cover various aspects of data analytics, including data querying and transformation, data model implementation and management, and data exploration and visualization. They will gain practical knowledge in using Microsoft Purview, Azure Synapse Analytics, and Power BI to build robust and effective analytics solutions.
A significant emphasis of the DP-500 course is placed on leveraging Microsoft Purview, a data governance and cataloging service. Students will learn how to effectively discover, classify, and track the lineage of their data assets, ensuring data quality, compliance, and security.
The course also covers Azure Synapse Analytics, an integrated analytics service that encompasses data ingestion, storage, and processing capabilities. Students will gain expertise in using Azure Synapse Analytics to implement and manage data analytics workflows, perform complex data transformations, and execute advanced analytical queries at scale.
Furthermore, the course introduces Power BI, a leading business intelligence and data visualization tool. Students will learn how to leverage Power BI to create interactive dashboards and reports, enabling them to effectively present and communicate insights derived from data.
By the end of the DP-500 course, students will have developed advanced skills in performing data analytics at scale. They will be proficient in implementing and managing a data analytics environment, conducting data queries and transformations, managing data models, and exploring and visualizing data. Through the use of Microsoft Purview, Azure Synapse Analytics, and Power BI, students will be equipped to build comprehensive and impactful analytics solutions.
Candidates for this DP 500 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.
Job role: Data Analyst
Explore Azure data services for modern analytics
Describe the Azure data ecosystem for analytics
Understand concepts of data analytics
- Describe types of data analytics
- Understand the data analytics process
Explore data analytics at scale
- Explore data job roles in analytics
- Understand tools for scaling analytics solutions
Introduction to Microsoft Purview
- 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.
Discover trusted data using Microsoft Purview
- Browse, search, and manage data catalog assets.
- Use data catalog assets with Power BI.
- Use Microsoft Purview in Azure Synapse Studio.
Catalog data artifacts by using Microsoft Purview
Describe asset classification in Microsoft Purview.
Manage Power BI assets by using 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.
Integrate Microsoft Purview and Azure Synapse Analytics
- 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.
Introduction to Azure Synapse Analytics
- Identify the business problems that Azure Synapse Analytics addresses.
- Describe core capabilities of Azure Synapse Analytics.
- Determine when to use Azure Synapse Analytics.
Use Azure Synapse serverless SQL pool to query files in a data lake
- 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
Analyze data with Apache Spark in Azure Synapse Analytics
- 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.
Analyze data in a relational data warehouse
- 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.
Choose a Power BI model framework
- 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.
Understand scalability in Power BI
- Describe the importance of building scalable data models
- Implement Power BI data modeling best practices
- Use the Power BI large dataset storage format
Create and manage scalable Power BI dataflows
- Describe Power BI dataflows and use cases.
- Describe best practices for implementing Power BI dataflows.
- Create and consume Power BI dataflows.
Create Power BI model relationships
- Understand how model relationship work.
- Set up relationships.
- Use DAX relationship functions.
- Understand relationship evaluation.
Use DAX time intelligence functions in Power BI Desktop models
- Define time intelligence.
- Use common DAX time intelligence functions.
- Create useful intelligence calculations.
Create calculation groups
- Explore how calculation groups work.
- Maintain calculation groups in a model.
- Use calculation groups in a Power BI report.
Enforce Power BI model security
- 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.
Use tools to optimize Power BI performance
- Optimize queries using performance analyzer.
- Troubleshoot DAX performance using DAX Studio.
- Optimize a data model using Tabular Editor.
Understand advanced data visualization concepts
- 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.
Monitor data in real-time with Power BI
- Describe Power BI real-time analytics.
- Set up automatic page refresh.
- Create real-time dashboards.
- Set up auto-refresh paginated reports.
Create paginated reports
- Get data.
- Create a paginated report.
- Work with charts and tables on the report.
- Publish the report.
Provide governance in a Power BI environment
- 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
Facilitate collaboration and sharing in Power BI
- Understand the differences between My workspace, workspaces, and apps
- Describe new workspace capabilities and how they improve the user experience
- Anticipate migration impact to Power BI users
- Share, publish to the web, embed links and secure Power BI reports, dashboards, and content
Monitor and audit usage
- Discover what usage metrics are available through the Power BI admin portal
- Optimize use of usage metrics for dashboards and reports
- Distinguish between audit logs and the activity logs
Provision Premium capacity in Power BI
- 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.
Establish a data access infrastructure in Power BI
- 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.
Broaden the reach of Power BI
- 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
Automate Power BI administration
- 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
Build reports using Power BI within Azure Synapse Analytics
- Describe the Power BI and Synapse workspace integration
- Understand Power BI data sources
- Describe optimization options
- Visualize data with serverless SQL pools
Design a Power BI application lifecycle management strategy
- Outline the application lifecycle process.
- Choose a source control strategy.
- Design a deployment strategy.
Create and manage a Power BI deployment pipeline
- 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 and manage Power BI assets
- Create specialized datasets.
- Create live and DirectQuery connections.
- Use Power BI service lineage view.
- Use XMLA endpoint to connect datasets.
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.
Q. What is DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI Training?
A. DP 500 is a training program offered by Microsoft that focuses on designing and implementing enterprise-scale analytics solutions using Microsoft Azure and Microsoft Power BI. It provides in-depth knowledge and skills required to architect and deploy analytics solutions that can handle large volumes of data and meet the needs of modern organizations.
Q. Who is this training program for?
A. The DP500 training program is designed for data professionals, solution architects, and developers who want to learn how to design and implement analytics solutions at an enterprise scale. It is suitable for individuals who have experience with Azure and Power BI and want to expand their knowledge to create robust analytics solutions.
Q. What are the key topics covered in the training?
A. The training covers a wide range of topics, including:
- Designing and implementing Azure data storage solutions
- Developing data processing solutions using Azure services
- Designing and implementing data security and compliance strategies
- Designing and implementing Power BI data models
- Designing and implementing Power BI reports and dashboards
- Optimizing and troubleshooting Power BI solutions
Q. Do I need any prerequisites to attend this training?
A. Yes, to get the most out of the DP 500 training, it is recommended to have foundational knowledge and experience in Microsoft Azure, Microsoft Power BI, and data analytics concepts. Familiarity with data storage, data processing, and Power BI modeling will be beneficial.
Q. What are the benefits of completing this training program?
A. By completing this training program, you will:
- Gain an in-depth understanding of designing and implementing enterprise-scale analytics solutions using Microsoft Azure and Power BI.
- Acquire the skills to architect and deploy robust data storage, processing, and visualization solutions.
- Learn best practices for data security, compliance, and optimization in an enterprise context.
- Enhance your ability to design and implement data models, reports, and dashboards using Power BI.
- Become proficient in troubleshooting and optimizing Power BI solutions.
Q. How is the training delivered?
A. The DP 500 training can be delivered through various methods, including in-person instructor-led training, virtual instructor-led training.
Q. How long does the training program typically last?
A. The duration of the training program can vary depending on the delivery method and the depth of coverage. In-person or virtual instructor-led training programs typically span several days, covering the comprehensive content. Self-paced online modules may offer flexibility in terms of duration, allowing learners to progress at their own pace.
Q. How can I enroll in the DP 500 training program?
A. To enroll in the DP 500 training program, you can visit the Microsoft Learning website
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This course comes with following benefits:
- Practice Labs.
- Get Trained by Microsoft Certified Trainers (MCT).
- Access to the recordings of your class sessions for 90 days.
- Digital courseware
- Experience 24*7 learner support.
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