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