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.
Who should attend
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 Microsoft Certified: 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 Microsoft Certified: Data Analyst Associate.
- Implement and manage a data analytics environment
- Query and transform data
- Implement and manage data models
- Explore and visualize data
- Introduction to data analytics on Azure
- Govern data across an enterprise
- Model, query, and explore data in Azure Synapse
- Prepare data for tabular models in Power BI
- Design and build scalable tabular models
- Optimize enterprise-scale tabular models
- Implement advanced data visualization techniques by using Power BI
- Implement and manage an analytics environment
- Manage the analytics development lifecycle
- Integrate an analytics platform into an existing IT infrastructure