
Module: Explore Azure data services for modern analytics
Module: Understand concepts of data analytics
Module: Explore data analytics at scale
Module: Introduction to Microsoft Purview
Module: Discover trusted data using Microsoft Purview
Module: Catalog data artifacts by using Microsoft Purview
Module: Manage Power BI assets by using Microsoft Purview
Module: Integrate Microsoft Purview and Azure Synapse Analytics
Module: Introduction to Azure Synapse Analytics
Module: Use Azure Synapse serverless SQL pool to query files in a data lake
Module: Analyze data with Apache Spark in Azure Synapse Analytics
Module: Analyze data in a relational data warehouse
Module: Choose a Power BI model framework
Module: Understand scalability in Power BI
Module: Create and manage scalable Power BI dataflows
Module: Create Power BI model relationships
Module: Use DAX time intelligence functions in Power BI Desktop models
Module: Create calculation groups
Module: Enforce Power BI model security
Module: Use tools to optimize Power BI performance
Module: Understand advanced data visualization concepts
Module: Monitor data in real-time with Power BI
Module: Create paginated reports
Module: Provide governance in a Power BI environment
Module: Facilitate collaboration and sharing in Power BI
Module: Microsoft Power Platform
Module: Monitor and audit usage
Module: Provision Premium capacity in Power BI
Module: Establish a data access infrastructure in Power BI
Module: Broaden the reach of Power BI
Module: Automate Power BI administration
Module: Build reports using Power BI within Azure Synapse Analytics
Module: Design a Power BI application lifecycle management strategy
Module: Create and manage a Power BI deployment pipeline
Module: Create and manage Power BI assets
Candidates for this 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.
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.