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

Category

Power BI

Rating
4.8
(4.8)
Price

$2195
Per Participant

Course Description

This DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI 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 DP-500 training, students will use Microsoft Purview, Azure Synapse Analytics, and Power BI to build analytics solutions.

Prerequisites for this training

Who should attend this course?

  • Candidates should have experience designing, developing, and deploying enterprise-scale data analytics solutions. Candidates should specifically possess extensive Power BI skills, including maintaining data repositories, processing data both on- and offline, and working with Power Query and Data Analysis Expressions (DAX).
  • Additionally, they should be adept in consuming data from Azure Synapse Analytics and have knowledge of querying relational databases, using Transact-SQL (T-SQL) to analyze data, and visualizing data.

Microsoft Certified Partner

Microtek Learning is a Microsoft Certified Partner for Learning Solutions. This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).

Schedules

GTR

Feb 21, 2023

9:00 am - 5:30 pm EST
Online

Mar 07, 2023

9:00 am - 5:30 pm EST
Online
GTR

Mar 21, 2023

9:00 am - 5:30 pm EST
Online
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What you will learn

  • Setup and administration of a data analytics environment
  • Data transformation and query
  • Manage and implement data models
  • Investigate and display data

Curriculum

  • 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
  • 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.
  • Identify the business problems that Azure Synapse Analytics addresses.
  • Describe core capabilities of Azure Synapse Analytics.
  • Determine when to use 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
  • 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.
  • 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.
  • 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
  • Describe Power BI dataflows and use cases.
  • Describe best practices for implementing Power BI dataflows.
  • Create and consume Power BI dataflows.
  • Understand how model relationship work.
  • Set up relationships.
  • Use DAX relationship functions.
  • Understand relationship evaluation.
  • 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.
  • 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.
  • Optimize queries using performance analyzer.
  • Troubleshoot DAX performance using DAX Studio.
  • Optimize a data model using Tabular Editor.
  • 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 to 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 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
  • 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.
  • What Exam Do I Need To Get Certified?

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

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    • Official Training Course Student Handbook
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    • Real-world knowledge activities and scenarios
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    • Practice Tests
    • Knowledge acquisition and exam-oriented
    • Interactive online course.
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    Course Details

    • Start Date: Feb 21, 2023
    • Duration: 4 Days
    • Skill Level: Intermediate
    • Enrolled: 2904
    • Price: $2195
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