Coursera

Data Modeling in Power BI (Coursera)

Offered by Microsoft,
Data Modeling in Power BI (Coursera)

This course forms part of the Microsoft Power BI Analyst Professional Certificate. This Professional Certificate consists of a series of courses that offers a good starting point for a career in data analysis using Microsoft Power BI.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

In this course, you'll learn how to use Power BI to create and maintain relationships in a data model and form a model using multiple Schemas. You'll explore the basics of DAX, Power BI's expression language, and add calculations to your model to create elements and analysis in Power BI. You'll discover how to configure the model to support Power BI features for insightful visualizations, analysis, and optimization.
After completing this course you'll be able to:

  • Create and maintain relationships in a data model.
  • Form a model using a Star Schema
  • Write calculations DAX to create elements and analysis in Power BI
  • Create calculated columns and measures in a model
  • Perform useful time intelligence calculations in DAX
  • Optimize performance in a Power BI model

This is also a great way to prepare for the Microsoft PL-300 exam. By passing the PL-300 exam, you’ll earn the Microsoft Power BI Data Analyst certification.
This course is part of the Microsoft Power BI Data Analyst Professional Certificate.

What you'll learn

  • How to form a model using a Star Schema.
  • How to write calculations DAX to create elements and analysis in Power BI.
  • How to optimize performance in a Power BI model.

Syllabus

Concepts for data modeling
Module 1
This module introduces data modeling and the schemas used to create them.

Using Data Analysis Expressions (DAX) in Power BI
Module 2
This module introduces the learner to the DAX (Data Analysis Expressions) language. The module explores the syntax of DAX using multiple business use cases. The module also integrates DAX with previous lessons on database tables and their use and introduces the concept of time intelligence.

Optimize a model for performance in Power BI
Module 3
This module explores the optimization process and examines the tools and methods to achieve this in Power BI, including using performance analyzer and DirectQuery features. This module also dives deeper into DAX and its use in the real world.

Final project and assessment: Modeling data in Power BI
Module 4
In this module, you will be assessed on the key skills covered in the course. This module summarizes the course and reflects on the primary learning objectives. The module also contains the project for the course, which encapsulates the learning into a practical whole.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Business Intelligence Concepts, Tools, and Applications (Coursera) Coursera
University of Colorado System

Business Intelligence Concepts, Tools, and Applications (Coursera)

Statistics & Data Analysis Data Science

This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer. You’ll have the opportunity to work with large data sets in a data warehouse environment and will learn the use of MicroStrategy's Online Analytical Processing (OLAP) and Visualization capabilities to create visualizations and dashboards.

Jun 8th 2026
5-12 Weeks
Data Analysis Decision Making Business Intelligence
Details
Bioinformatic Methods II (Coursera) Coursera
University of Toronto

Bioinformatic Methods II (Coursera)

Sci: Biology & Life Sciences Health & Society

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on.

Jun 8th 2026
5-12 Weeks
Biology Bioinformatics Molecular Biology
Details
Predictive Modeling and Analytics (Coursera) Coursera
University of Colorado Boulder

Predictive Modeling and Analytics (Coursera)

Statistics & Data Analysis Data Science

Welcome to the second course in the Data Analytics for Business specialization! This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business.

Jun 8th 2026
4 Weeks
Data Analysis Analytics Data Cleaning
Details
Reproducible Research (Coursera) Coursera
Johns Hopkins University

Reproducible Research (Coursera)

Statistics & Data Analysis Data Science

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations.

Jun 8th 2026
4 Weeks
Data Analysis Data Science Reproducible Research
Details
The Data Scientist's Toolbox (Coursera) Coursera
Johns Hopkins University

The Data Scientist's Toolbox (Coursera)

Statistics & Data Analysis Data Science

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

Jun 8th 2026
4 Weeks
Data Github Data Analysis
Details
Data Visualization (Coursera) Coursera
University of Illinois at Urbana-Champaign

Data Visualization (Coursera)

Statistics & Data Analysis Data Science

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based classification and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.

Jun 8th 2026
4 Weeks
Data Mining Numerical Analysis Data Visualization
Details
Data Analytics for Lean Six Sigma (Coursera) Coursera
University of Amsterdam

Data Analytics for Lean Six Sigma (Coursera)

Statistics & Data Analysis Data Science

Welcome to this course on Data Analytics for Lean Six Sigma. In this course you will learn data analytics techniques that are typically useful within Lean Six Sigma improvement projects. At the end of this course you are able to analyse and interpret data gathered within such a project. You will be able to use Minitab to analyse the data. I will also briefly explain what Lean Six Sigma is.

Jun 8th 2026
5-12 Weeks
Testing Lean Six Sigma Data Visualization
Details
Introduction to Data Analysis Using Excel (Coursera) Coursera
Rice University

Introduction to Data Analysis Using Excel (Coursera)

Statistics & Data Analysis

The use of Excel is widespread in the industry. It is a very powerful data analysis tool and almost all big and small businesses use Excel in their day to day functioning. This course is designed to give you a working knowledge of Excel with the aim of getting to use it for more advance topics in Business Statistics. The course is designed keeping in mind two kinds of learners - those who have very little functional knowledge of Excel and those who use Excel regularly but at a peripheral level and wish to enhance their skills.

Jun 8th 2026
4 Weeks
Spreadsheets Excel Data Analysis
Details
Marketing Analytics (Coursera) Coursera
University of Virginia

Marketing Analytics (Coursera)

Marketing & Communication Business

Organizations large and small are inundated with data about consumer choices. But that wealth of information does not always translate into better decisions. Knowing how to interpret data is the challenge -- and marketers in particular are increasingly expected to use analytics to inform and justify their decisions. Marketing analytics enables marketers to measure, manage and analyze marketing performance to maximize its effectiveness and optimize return on investment (ROI). Beyond the obvious sales and lead generation applications, marketing analytics can offer profound insights into customer preferences and trends, which can be further utilized for future marketing and business decisions.

Jun 8th 2026
5-12 Weeks
Marketing Regression Data Analysis
Details
Foundations of strategic business analytics (Coursera) Coursera
ESSEC Business School

Foundations of strategic business analytics (Coursera)

Management & Leadership Business

Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering.

Jun 8th 2026
4 Weeks
Data Analysis Analytics Presentations
Details
Machine Learning Foundations: A Case Study Approach (Coursera) Coursera
University of Washington

Machine Learning Foundations: A Case Study Approach (Coursera)

Statistics & Data Analysis Data Science

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies.

Jun 8th 2026
5-12 Weeks
Python Machine Learning Clustering
Details