Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI (DP-500) - Dag

Je bent data-analist en wilt je kennis en vaardigheden van werken met data-analyses naar een hoger niveau tillen.

Tijdens deze training wordt voortgebouwd op bestaande kennis met data-analyses. Je leert een omgeving voor data-analyse implementeren en beheren en kunt hierbinnen werken met de data: je kunt ze opvragen, bewerken en visualiseren. Ook datamodellen kun je toepassen op je gegevens. 

Admission

Voor het deelnemen aan deze training dien je over de volgende vaardigheden te beschikken:

• Behendig met Power BI
• Beheren van gegevensopslagplaatsen en gegevensverwerking in de cloud en op locatie
• Ervaring met Power Query, Data Analysis Expressions (DAX) en Azure Synapse Analytics
• Ervaring met het opvragen van relationele databases, het analyseren van gegevens met behulp van Transact-SQL (T-SQL) en het visualiseren van gegevens

Graduation

Objectives

Het gedegen programma van deze klassikale training is erop gericht dat je het geleerde direct kunt toepassen in je praktijksituatie. De zeer ervaren en gecertificeerde trainer van Computrain behandelt de theorie en laat met diverse demonstraties zien hoe deze toe te passen in de praktijk. Je gaat aan de slag met verschillende oefeningen waardoor een optimale verwerking van de leerstof wordt bewerkstelligd. De verhouding tussen theorie en praktijk is ongeveer 50-50.

Program guide

Inhoud Govern and administer a data analytics environment

• Manage Power BI assets by using Azure Purview
• Identify data sources in Azure by using Azure Purview
• Recommend settings in the Power BI admin portal
• Recommend a monitoring and auditing solution for a data analytics environment, including Power BI REST API and PowerShell cmdlets

Integrate an analytics platform into an existing IT infrastructure

• Identify requirements for a solution, including features, performance, and licensing
  strategy
• Configure and manage Power BI capacity
• Recommend and configure an on-premises gateway in Power BI
• Recommend and configure a Power BI tenant or workspace to integrate with Azure Data Lake Storage Gen2
• Integrate an existing Power BI workspace into Azure Synapse Analytics

Manage the analytics development lifecycle

• Commit code and artifacts to a source control repository in Azure Synapse Analytics
• Recommend a deployment strategy for Power BI assets
• Recommend a source control strategy for Power BI assets
• Implement and manage deployment pipelines in Power BI
• Perform impact analysis of downstream dependencies from dataflows and datasets
• Pecommend automation solutions for the analytics development lifecycle, including Power BI REST API and PowerShell cmdlets
• Deploy and manage datasets by using the XMLA endpoint
• Create reusable assets, including Power BI templates, Power BI data source (.pbids) files, and shared datasets

Query data by using Azure Synapse Analytics

• Identify an appropriate Azure Synapse pool when analyzing data
• Recommend appropriate file types for querying serverless SQL pools
• Query relational data sources in dedicated or serverless SQL pools, including querying partitioned data sources
• Use a machine learning PREDICT function in a query

Ingest and transform data by using Power BI

• Identify data loading performance bottlenecks in Power Query or data sources
• Implement performance improvements in Power Query and data sources
• Create and manage scalable Power BI dataflows
• Identify and manage privacy settings on data sources
• Create queries, functions, and parameters by using the Power Query Advanced Editor
• Query advanced data sources, including JSON, Parquet, APIs, and Azure Machine Learning models

Design and build tabular models

• Choose when to use DirectQuery for Power BI datasets
• Choose when to use external tools, including DAX Studio and Tabular Editor 2
• Create calculation groups
• Write calculations that use DAX variables and functions, for example handling blanks or errors, creating virtual relationships, and working with iterators
• Design and build a large format dataset
• Design and build composite models, including aggregations
• Design and implement enterprise-scale row-level security and object-level security

Optimize enterprise-scale data models

• Identify and implement performance improvements in queries and report visuals
• Troubleshoot DAX performance by using DAX Studio
• Optimize a data model by using Tabular Editor 2
• Analyze data model efficiency by using VertiPaq Analyzer
• Implement incremental refresh
• Optimize a data model by using denormalization

Explore data by using Azure Synapse Analytics

• Explore data by using native visuals in Spark notebooks
• Explore and visualize data by using the Azure Synapse SQL results pane

Visualize data by using Power BI

• Create and import a custom report theme
• Create R or Python visuals in Power BI
• Connect to and query datasets by using the XMLA endpoint
• Design and configure Power BI reports for accessibility
• Enable personalized visuals in a report
• Configure automatic page refresh
• Create and distribute paginated reports in Power BI Report Builder

Course schedule

4 dagen