Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI

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

 

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.

Job role: Data Analyst

 

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.

 

Topics

 

Module 1: Introduction to data analytics on Azure

Module 2: Govern data across an enterprise

Module 3: Model, query, and explore data in Azure Synapse

Module 4: Prepare data for tabular models in Power BI

Module 5: Design and build scalable tabular models

Module 6: Optimize enterprise-scale tabular models

Module 7: Implement advanced data visualization techniques by using Power BI

Module 8: Implement and manage an analytics environment

Module 9: Manage the analytics development lifecycle

Module 10: Integrate an analytics platform into an existing IT infrastructure