Harnessing the Power of Data with Power BI (Coursera)

Offered by Microsoft,
Harnessing the Power of Data with 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. In this course, you’ll learn about the role of a data analyst and the main stages involved in the data analysis process with a focus on applying them using Microsoft Power BI.

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

After completing this course, you’ll be able to:  
• Describe how data is produced and gathered in businesses and organizations. 
• Outline the role of data in creating data-driven decisions and successful business outcomes. 
• Classify key stages in the data analysis process. 
• Recognize the skills needed by a Power BI analyst and the tools they use. 
• List the tasks performed by a Power BI Data Analyst. 
• Recognize the components of Power BI. 
This course is part of the Microsoft Power BI Data Analyst Professional Certificate.

What you'll learn

  • How to recognize and use the key data analysis components of Microsoft Power BI.
  • Understand a Power BI data analyst's skills, tasks, and tools.
  • Describe the different stages in the data analysis process that result in data-driven decisions.

Syllabus

Data analysis in business
Module 1
This module introduces the learner to the role of a Data Analyst, key data analysis concepts and how data plays an important role in business. The learner is briefly introduced to Power BI as tool for data analysis.

The right tools for the job
Module 2
This module introduces the learner to data collection, data sources, the ETL process and the importance of evaluating data for analysis

Final project and assessment: Harnessing the power of data in Power BI
Module 3
In this module, you will be assessed on the key skills covered in the Course.

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

Related Courses

Text Retrieval and Search Engines (Coursera) Coursera
University of Illinois at Urbana-Champaign

Text Retrieval and Search Engines (Coursera)

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.

Jun 8th 2026
5-12 Weeks
Introducción a Data Science: Programación Estadística con R (Coursera) Coursera
Universidad Nacional Autónoma de México

Introducción a Data Science: Programación Estadística con R (Coursera)

Este curso te proporcionará las bases del lenguaje de programación estadística R, la lengua franca de la estadística, el cual te permitirá escribir programas que lean, manipulen y analicen datos cuantitativos. Te explicaremos la instalación del lenguaje; también verás una introducción a los sistemas base de gráficos y al paquete para graficar ggplot2, para visualizar estos datos. Además también abordarás la utilización de uno de los IDEs más populares entre la comunidad de usuarios de R, llamado RStudio.

Jun 8th 2026
4 Weeks
The Data Scientist's Toolbox (Coursera) Coursera
Johns Hopkins University

The Data Scientist's Toolbox (Coursera)

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
Reproducible Research (Coursera) Coursera
Johns Hopkins University

Reproducible Research (Coursera)

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
Introduction to Data Analysis Using Excel (Coursera) Coursera
Rice University

Introduction to Data Analysis Using Excel (Coursera)

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
Pattern Discovery in Data Mining (Coursera) Coursera
University of Illinois at Urbana-Champaign

Pattern Discovery in Data Mining (Coursera)

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 data-driven phrase mining 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
Communicating Business Analytics Results (Coursera) Coursera
University of Colorado Boulder

Communicating Business Analytics Results (Coursera)

The analytical process does not end with models than can predict with accuracy or prescribe the best solution to business problems. Developing these models and gaining insights from data do not necessarily lead to successful implementations. This depends on the ability to communicate results to those who make decisions.

Jun 8th 2026
4 Weeks
Introduction to Data Science in Python (Coursera) Coursera
University of Michigan

Introduction to Data Science in Python (Coursera)

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

Jun 8th 2026
4 Weeks
Infonomics II: Business Information Management and Measurement (Coursera) Coursera
University of Illinois at Urbana-Champaign

Infonomics II: Business Information Management and Measurement (Coursera)

Even decades into the Information Age, accounting practices yet fail to recognize the financial value of information. Moreover, traditional asset management practices fail to recognize information as an asset to be managed with earnest discipline. This has led to a business culture of complacence, and the inability for most organizations to fully leverage available information assets. This second course in the two-part Infonomics series explores how and why to adapt well-honed asset management principles and practices to information, and how to apply accepted and new valuation models to gauge information’s potential and realized economic benefits.

Jun 10th 2026
4 Weeks
Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud (Coursera) Coursera
University of Illinois at Urbana-Champaign

Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud (Coursera)

Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Cloud applications and data analytics represent a disruptive change in the ways that society is informed by, and uses information.

Jun 8th 2026
4 Weeks
Introduction to Probability and Data with R (Coursera) Coursera
Duke University

Introduction to Probability and Data with R (Coursera)

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Jun 8th 2026
5-12 Weeks