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

2,380 USD
4 Days
Classroom Training, Online Training

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  • Guaranteed to Run
    Date: 5-Mar-2024 to 8-Mar-2024
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: united
    Price: 2,380 USD
  • Date: 18-Mar-2024 to 21-Mar-2024
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: LearnQuest
    Price: 2,380 USD
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Course Description


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.






    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.


Explore Azure data services for modern analytics Understand concepts of data analytics
  • Understand data analytics types
  • Explore the data analytics process
  • Understand types of data and data storage
Explore data analytics at scale
  • Explore data team roles and responsibilities
  • Review tasks and tools for data analysts
  • Scale analytics with Azure Synapse Analytics and Power BI
  • Strategies to scale analytics
Introduction to Microsoft Purview
  • What is Microsoft Purview?
  • How Microsoft Purview works
  • When to use Microsoft Purview
Discover trusted data using Microsoft Purview
  • Search for assets
  • Browse assets
  • Use assets with Power BI
  • Integrate with Azure Synapse Analytics
Catalog data artifacts by using Microsoft Purview
  • Register and scan data
  • Classify and label data
  • Search the data catalog
Manage Power BI assets by using Microsoft Purview
  • Register and scan a Power BI tenant
  • Search and browse Power BI assets
  • View Power BI metadata and lineage
Integrate Microsoft Purview and Azure Synapse Analytics
  • Catalog Azure Synapse Analytics data assets in Microsoft Purview
  • Connect Azure purview to an Azure Synapse Analytics workspace
  • Search a Purview catalog in Synapse Studio
  • Track data lineage in pipelines
  • Exercise - Integrate Azure Synapse Analytics and Microsoft Purview
Introduction to Azure Synapse Analytics
  • What is Azure Synapse Analytics
  • How Azure Synapse Analytics works
  • When to use Azure Synapse Analytics
  • Exercise - Explore Azure Synapse Analytics
Analyze data with Apache Spark in Azure Synapse Analytics
  • Get to know Apache Spark
  • Use Spark in Azure Synapse Analytics
  • Analyze data with Spark
  • Visualize data with Spark
  • Exercise - Analyze data with Spark
Use Azure Synapse serverless SQL pool to query files in a data lake
  • Understand Azure Synapse serverless SQL pool capabilities and use cases
  • Query files using a serverless SQL pool
  • Create external database objects
  • Exercise - Query files using a serverless SQL pool
Analyze data in a relational data warehouse
  • Design a data warehouse schema
  • Create data warehouse tables
  • Load data warehouse tables
  • Query a data warehouse
  • Exercise - Explore a data warehouse
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 a model framework
Understand scalability in Power BI
  • Describe the significance of scalable models
  • Implement Power BI data modeling best practices
  • Configure large datasets
  • Exercise: Create a star schema model
Create and manage scalable Power BI dataflows
  • Define use cases for dataflows
  • Create reusable assets
  • Implement best practices
  • Exercise: Create a dataflow
Create Power BI model relationships
  • Understand model relationships
  • Set up relationships
  • Use DAX relationship functions
  • Understand relationship evaluation
  • Exercise: Work with model relationships
Use DAX time intelligence functions in Power BI Desktop models
  • Use DAX time intelligence functions
  • Additional time intelligence calculations
Create calculation groups
  • Understand calculation groups
  • Explore calculation groups features and usage
  • Create calculation groups in a model
  • Exercise: Create calculation groups
Enforce Power BI model security
  • Restrict access to Power BI model data
  • Restrict access to Power BI model objects
  • Apply good modeling practices
  • Exercise: Enforce model security
Use tools to optimize Power BI performance
  • Use Performance analyzer
  • Troubleshoot DAX performance by using DAX Studio
  • Optimize a data model by using Best Practice Analyzer
  • Exercise: Use tools to optimize Power BI performance
Understand advanced data visualization concepts
  • Create and import a custom report theme
  • Enable personalized visuals in a report
  • Design and configure Power BI reports for accessibility
  • Create custom visuals with R or Python
  • Review report performance using Performance Analyzer
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
  • Exercise: Monitor data in real-time with Power BI
Create paginated reports
  • Introduction to paginated reports
  • Get data
  • Create a paginated report
  • Work with charts on the report
  • Publish the report
Provide governance in a Power BI environment
  • Elements of data governance
  • Configure tenant settings
  • Deploy organizational visuals
  • Manage embed codes
  • Help and support settings
Facilitate collaboration and sharing in Power BI
  • Workspaces evolved
  • Impact to Power BI users
  • Permissions in workspaces v2
  • Apps in Power BI
  • Share
  • Publish to web
  • Embed and link in portals
  • Data sensitivity labels
  • Data privacy
Monitor and audit usage
  • Usage metrics for dashboards and reports
  • Usage metrics for dashboards and reports - new version
  • Audit logs
  • Activity log
Provision Premium capacity in Power BI
  • Premium resource management
  • Supporting multi geographies
  • Bring your own key (BYOK)
  • Featured external tools
Establish a data access infrastructure in Power BI
  • Personal gateways versus enterprise gateways
  • How data is refreshed
  • Gateway network requirements
  • Where to install gateway?
  • Establish high availability gateways
  • Establish load balancing of gateways
  • Gateway performance monitoring documentation
  • Multiple data sources per gateway
  • Manage gateway users
  • Active Directory user mapping with custom property lookup
Broaden the reach of Power BI
  • REST API custom development
  • Provision a Power BI embedded capacity
  • Dataflow introduction
  • Dataflow explained
  • Create a Dataflow
  • Dataflow capabilities on Power BI Premium
  • Template apps - install packages
  • Template apps - installed entities
  • Template app governance
Automate Power BI administration
  • REST API - Power BI service
  • Microsoft Power BI cmdlets for Windows PowerShell and PowerShell core
  • Install and use the Power BI cmdlet
  • Test REST API calls
  • Script typical administrator tasks
  • Lab
Build reports using Power BI within Azure Synapse Analytics
  • Describe the Power BI and Synapse workspace integration
  • Exercise - Connect to Power BI from Synapse
  • Understand Power BI data sources
  • Exercise - Create a new data source to use in Power BI
  • Exercise - Create a new Power BI report in Synapse Studio
  • Describe Power BI optimization options
  • Exercise - Improve performance with materialized views and result-set caching
  • Visualize data with serverless SQL pools
Design a Power BI application lifecycle management strategy
  • Define application lifecycle management
  • Recommend a source control strategy
  • Design a deployment strategy
Create and manage a Power BI deployment pipeline
  • Understand the deployment process
  • Create a deployment pipeline
  • Assign a workspace
  • Deploy content
  • Work with deployment pipelines
Create and manage Power BI assets
  • Create reusable Power BI assets
  • Explore Power BI assets using lineage view
  • Manage a Power BI dataset using XMLA endpoint
  • Exercise: Create reusable Power BI assets
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