About This Course
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.
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.
At Course Completion
After completing this course, students will be able to:
Before attending this course, it is recommended that students have:
Module 1: Introduction to data analytics on Azure
This module explores key concepts of data analytics, including types of analytics, data, and storage. Students will explore the analytics process and tools used to discover insights and learn about the responsibilities of an enterprise data analyst and what tools are available to build scalable solutions.
Lesson
After completing this module, students will be able to:
Module 2: Govern data across an enterprise
This module explores the role of an enterprise data analyst in organizational data governance. Students will explore the use of Microsoft Purview to register and catalog data assets, to discover trusted assets for reporting, and to scan a Power BI environment.
Lesson
After completing this module, students will be able to:
Module 3: Model, query, and explore data in Azure Synapse
This module explores the use of Azure Synapse Analytics for exploratory data analysis. Students will explore the capabilities of Azure Synapse Analytics including the basics of data warehouse design, querying data using T-SQL, and exploring data using Spark notebooks.
Lesson
Lab : Query data in Azure
Lab : Explore data in Spark notebooks
Lab : Create a star schema model
After completing this module, students will be able to:
Module 4: Prepare data for tabular models in Power BI
This module explores the fundamental elements of preparing data for scalable analytics solutions using Power BI. Students will explore model frameworks, considerations for building data models that will scale, Power Query optimization techniques, and the implementation of Power BI dataflows.
Lesson
Lab : Create a dataflow
After completing this module, students will be able to:
Module 5: Design and build scalable tabular models
This module explores the critical underlying aspects of tabular modeling for building Power BI models that can scale. Students will learn about model relationships and model security, working with direct query, and using calculation groups.
Lesson
Lab : Create model relationships
Lab : Enforce model security
Lab : Design and build tabular models
Lab : Create calculation groups
Lab : Use tools to optimize Power BI performance
After completing this module, students will be able to:
Module 6: Implement advanced data visualization techniques by using Power BI
This module explores data visualization concepts including accessibility, customization of core data models, real-time data visualization, and paginated reporting.
Lesson
Lab : Monitor data in real-time with Power BI
Lab : Create and distribute paginated reports in Power BI Report Builder
After completing this module, students will be able to:
Module 7: Implement and manage an analytics environment
This module explores key considerations for implementing and managing Power BI. Students will understand key recommendations for administration and monitoring of Power BI, including configuration and management of Power BI capacity.
Lesson
After completing this module, students will be able to:
Module 8: Manage the analytics development lifecycle
This module explores considerations for deployment, source control, and application lifecycle management of analytics solutions. Students will understand what to recommend and will be able to deploy and manage automated and reusable Power BI assets.
Lesson
Lab : Create reusable Power BI assets
After completing this module, students will be able to:
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