Insights of Power BI (Coursera)

Offered by Fractal Analytics,
Insights of Power BI (Coursera)

Today's business world is becoming increasingly data-driven. Small and large businesses use data to make decisions about sales, hiring, goals, and all areas they have data for. While most businesses have access to data of one type or another, it can be intimidating for an average business user to understand the data without a background in data analytics.

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

Microsoft’s Power BI takes the intimidation and hassle out of data analysis and visualization.
Throughout this course, you will identify errors in the datasets and diagnose them using data cleaning and transformation techniques to prepare them for reporting purposes. With a focus on practical applications, you will solve complex visualizations using the DAX operator and assess the visualizations to plan business-related decisions.
Whether you aspire to be a data analyst, a business intelligence professional, or a decision-maker relying on data-driven insights, this course will provide you with the necessary tools and knowledge to succeed.
This course is part of the Fractal Data Science Professional Certificate.

What you'll learn

  • Select and use relevant charts for appropriate data problems
  • Use PowerBI to connect with data belonging to diverse formats
  • Communicate key insights from business problem using Reports and Dashboards
  • Create advanced visualization on Power BI using DAX

Syllabus

Introduction to Power BI and Data Visualization
This module provides a comprehensive introduction to Power BI and data visualizations. Learners will explore the capabilities of Power BI and gain proficiency in creating impactful visualizations. Topics covered include installation and getting started with Power BI, various chart types, Power BI interface overview, comparison of reports and dashboards, and building a basic Power BI report. Throughout the module, learners will progress from understanding Power BI fundamentals to applying their knowledge in creating meaningful visualizations.

Transforming The Data Using Insights
This module, "Operations on Multiple Tables," covers essential techniques for handling and analyzing data across multiple tables. By delving into different cleaning techniques, students will gain proficiency in efficiently retrieving datasets that can be directly used for visualizations. The module goes beyond theoretical concepts by providing practical exercises using a real-world case study, allowing users to apply their problem-solving abilities in a hands-on manner. At the end of this module, students will discover how to enhance data models by gaining an understanding of Fact tables and Dimension tables. Upon completion of the module, students will be able to acquire the skills to effectively perform operations on multiple tables, ensuring clean, transformed, and relationship-driven data models for analysis.

Getting Started with DAX
In this module "DAX Operator", students will gain valuable skills to perform advanced calculations and data manipulations in Power BI. Students will explore various DAX functions and operators, understand their syntax and structure, and learn how to apply them effectively in Power BI. Additionally, they will also differentiate between calculated columns and measures, gaining insights into when to use each approach. In the end, students will have an in-depth understanding of the Row context and Filter context. Through practical examples and problem-solving exercises, students will develop a solid understanding of DAX fundamentals and their significance in data analysis.

Building Customized Reports and Dashboard
In this module, students will delve deeper and acquire skills and knowledge to create comprehensive reports and expanding their knowledge of utilizing DAX operators. They will learn essential skills to utilize diverse visualizations and address problem statements to deliver actionable insights. Furthermore, this module will emphasize the importance of designing and structuring the report to make it relevant for businesses. By mastering these skills, students will acquire the necessary tools to become an expert in the field of business intelligence and contribute to data-driven decision-making.

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

Related Courses

Necessary Condition Analysis (NCA) (Coursera) Coursera
Erasmus University Rotterdam

Necessary Condition Analysis (NCA) (Coursera)

Welcome to Necessary Condition Analysis (NCA). NCA analyzes data using necessity logic. A necessary condition implies that if the condition is not in place, there will be guaranteed failure of the outcome. The opposite however is not true; if the condition is in place, success of the outcome is not guaranteed.

Aug 3rd 2026
5-12 Weeks
Analyzing and Visualizing Data in Looker (Coursera) Coursera
Google Cloud

Analyzing and Visualizing Data in Looker (Coursera)

In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

Aug 3rd 2026
2 Weeks
Introduction to Statistics (Coursera) Coursera
Stanford University

Introduction to Statistics (Coursera)

Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning.

Aug 10th 2026
5-12 Weeks
Bioinformatic Methods II (Coursera) Coursera
University of Toronto

Bioinformatic Methods II (Coursera)

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.

Aug 3rd 2026
5-12 Weeks
Business Applications of Hypothesis Testing and Confidence Interval Estimation (Coursera) Coursera
Rice University

Business Applications of Hypothesis Testing and Confidence Interval Estimation (Coursera)

Confidence intervals and Hypothesis tests are very important tools in the Business Statistics toolbox. A mastery over these topics will help enhance your business decision making and allow you to understand and measure the extent of ‘risk’ or ‘uncertainty’ in various business processes. This course advances your knowledge about Business Statistics by introducing you to Confidence Intervals and Hypothesis Testing. These are done by easy to understand applications.

Aug 10th 2026
4 Weeks
Use Tableau for your Data Science Workflow (Coursera) Coursera
Edureka

Use Tableau for your Data Science Workflow (Coursera)

Learn Tableau fundamentals, advanced visualizations, and integration with data science tools. Elevate your skills in creating impactful dashboards. Enroll now for hands-on experience and master the art of data storytelling. Unlock the potential for advanced analytics, exploring correlations and trends within your data. Build interactive dashboards that tell compelling data stories, utilizing filters, parameters, and actions for user engagement.

Aug 10th 2026
1 Week
Data Visualization with Tableau Project (Coursera) Coursera
University of California, Davis

Data Visualization with Tableau Project (Coursera)

In this project-based course, you will follow your own interests to create a portfolio worthy single-frame viz or multi-frame data story that will be shared on Tableau Public. You will use all the skills taught in this Specialization to complete this project step-by-step, with guidance from your instructors along the way.

Aug 10th 2026
5-12 Weeks
Data intelligence for businesses and managers (Coursera) Coursera
Institut Mines-Telecom

Data intelligence for businesses and managers (Coursera)

With the proliferation of connected objects (computers, tablets, watches, etc.), huge masses of data are generated every second. This Big Data has led to the emergence of a data economy, where data is the main source of competitive advantage for companies. In this sense, data and its processing tools have become a strategic priority for companies, and the main gas pedal of their digital transformation.

Aug 10th 2026
5-12 Weeks
Python and Statistics for Financial Analysis (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Python and Statistics for Financial Analysis (Coursera)

Python is now becoming the number 1 programming language for data science. Due to python’s simplicity and high readability, it is gaining its importance in the financial industry. The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data.

Aug 10th 2026
4 Weeks
Applied Plotting, Charting & Data Representation in Python (Coursera) Coursera
University of Michigan

Applied Plotting, Charting & Data Representation in Python (Coursera)

This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework.

Aug 10th 2026
4 Weeks