Entwerfen und Implementieren von Analyselösungen auf Unternehmensebene mit MS Azure und MS Power BI

In diesem Training werden Methoden und Praktiken zur Durchführung erweiterter Datenanalysen im großen Stil behandelt. Die Trainingsteilnehmer*innen bauen auf vorhandenen Analyseerfahrungen auf und lernen, eine Datenanalyseumgebung zu implementieren und zu verwalten, Daten abzufragen und zu transformieren, Datenmodelle zu implementieren und zu verwalten sowie Daten zu untersuchen und zu visualisieren.
In diesem Training verwenden die Trainingsteilnehmer Microsoft Purview, Azure Synapse Analytics und Power BI, um Analyselösungen zu erstellen.

Explore Azure data services for modern analytics

• Understand the Azure data ecosystem
• Explore modern analytics solution architecture

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 Microsoft Purview to an Azure Synapse Analytics workspace
• Search a Purview catalog in Synapse Studio
• Track data lineage in pipelines

Introduction to Azure Synapse Analytics

• What is Azure Synapse Analytics
• How Azure Synapse Analytics works
• When to use Azure Synapse Analytics

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

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

Analyze data in a relational data warehouse

• Design a data warehouse schema
• Create data warehouse tables
• Load data warehouse tables
• Query 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

Create and manage scalable Power BI dataflows

• Define use cases for dataflows
• Create reusable assets
• Implement best practices

Create Power BI model relationships

• Understand model relationships
• Set up relationships
• Use DAX relationship functions
• Understand relationship evaluation

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

Enforce Power BI model security

• Restrict access to Power BI model data
• Restrict access to Power BI model objects
• Apply good modeling practices

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

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

Create paginated reports

• Get data
• Create a paginated report
• Work with charts on the report
• Publish the report
• Check your knowledge

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?

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
• 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

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

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

Die Kandidaten/Kandidatinen für diesen Training sollten über Fachkenntnisse im Entwerfen sowie in der Erstellung und Bereitstellung von Datenanalyselösungen auf Unternehmensebene verfügen. Kandidaten für diese Prüfung sollten insbesondere über fortgeschrittene Power BI-Kenntnisse verfügen, einschließlich der Verwaltung von Datenrepositorys und Datenverarbeitung in der Cloud und lokal, sowie mit der Verwendung von Power Query und Data Analysis Expressions (DAX) vertraut sein. Sie sollten auch mit der Nutzung von Daten aus Azure Synapse Analytics vertraut sein und Erfahrung mit der Abfrage relationaler Datenbanken, der Analyse von Daten mithilfe von Transact-SQL (T-SQL) und der Visualisierung von Daten besitzen.

• Grundlegende Kenntnisse der wichtigsten Datenkonzepte und deren Umsetzung mithilfe von Azure-Datendiensten. Weitere Informationen finden Sie unter Azure-Datengrundlagen.
• Erfahrung im Entwerfen und Erstellen skalierbarer Datenmodelle, mit dem Bereinigen und Transformieren von Daten sowie dem Ermöglichen erweiterter Analysefunktionen, die einen aussagekräftigen Geschäftswert bieten, mit Microsoft Power BI. Weitere Informationen finden Sie unter Power BI Data Analyst.