Power BI Data Analyst Associate Prep (Coursera)

Offered by SkillUp EdTech,
Power BI Data Analyst Associate Prep (Coursera)

This short course will guide you on preparing for the PL-300: Microsoft Power BI Data Analyst exam. This exam is the requirement for Microsoft Certified: Power BI Data Analyst Associate certification. The course provides you with a detailed understanding of the Power BI concepts, its features, and capabilities.

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

By the end of this course, you will be able to:

  • Describe how to prepare data for analysis by transforming, configuring, cleaning, and shaping it using Power BI.
  • Discuss the creation of data models in Power BI using a data model framework and Data Analysis Expressions (DAX) functions.
  • Explain how to design visually appealing reports using data visualization strategies in Power BI and perform data analytics using Analyze feature.
  • Examine how to create workspace, design interactive dashboards, and safeguard the data by configuring row-level security for datasets in Power BI.

The PL-300 exam is intended for data professionals who want to collaborate closely with business stakeholders, enterprise data analysts, and data engineers to identify and acquire data, transform the data, create data models, visualize data, and share assets using Power BI.
Having experience with data analysis, reporting, Power BI, proficiency in writing expressions by using Data Analysis Expressions (DAX), and understanding how to assess data quality is a must.

What you'll learn

  • Describe how to prepare data for analysis by transforming, configuring, cleaning, and shaping it using Power BI.
  • Discuss the creation of data models in Power BI using a data model framework and Data Analysis Expressions (DAX) functions.
  • Explain how to design visually appealing reports using data visualization strategies in Power BI and perform data analytics using Analyze feature.
  • Examine how to create workspace, design interactive dashboards, and safeguard the data by configuring row-level security for datasets in Power BI.

Syllabus

Data preparation and modeling in Power BI
The module begins with an overview of the features and components of Power BI that make it a great tool for data analysis. You’ll be able to explain how to retrieve data from different data sources and import it into Power BI by using Power Query. You’ll also learn how to clean and shape data for analysis purposes and load it into Power BI before getting into data modeling. Additionally, you will gain insight into Power BI data model frameworks, their benefits, limitations, and features that help optimize the selection of a Power BI data model. You will also learn to simplify the process of designing data models with an emphasis on the use of tables and dimensions and the significance of correct data granularity. Finally, you will gain insight into advanced data modeling features and how to perform advanced model calculations by using Data Analysis Expression (DAX) functions. You’ll also learn to add measures to Power BI Desktop models for enhancing the visualization of model data.

Data visualization and analysis in Power BI
In this module, you’ll explore various visualization strategies that enable you to implement effective data visualization. You will learn how to use core desktop visualization types to design visually appealing reports. Additionally, you will gain insight into formatting and configuring visualizations and discover techniques to perform data analytics by using the Analyze feature in Power BI. Finally, you’ll dive into how to use the Analytics feature for performing data analytics within Power BI, which helps you perform tasks such as identifying outliers, grouping data, and applying time series analysis.

Assets deployment and maintenance
In this module, you’ll explore asset deployment by creating a Power BI service workspace and dynamic dashboards. Additionally, you will learn how to manage and promote datasets and implement essential measures to ensure row-level security (RLS) in Power BI.

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

Related Courses

Learn SQL with Databricks (Coursera) Coursera
Edureka

Learn SQL with Databricks (Coursera)

Welcome to the Learn SQL with Databricks course, where you'll embark on a journey to acquire essential skills in database management, data analysis, and advanced data manipulation techniques. This course is meticulously designed to guide you through the intricacies of SQL, leveraging the powerful and versatile Databricks platform.

Oct 26th 2026
5-12 Weeks
Business intelligence and data analytics: Generate insights (Coursera) Coursera
Macquarie University

Business intelligence and data analytics: Generate insights (Coursera)

‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation.

Oct 19th 2026
5-12 Weeks
Big Data Analysis Deep Dive (Coursera) Coursera
Alibaba Cloud Academy

Big Data Analysis Deep Dive (Coursera)

The job market for architects, engineers, and analytics professionals with Big Data expertise continues to increase. The Academy’s Big Data Career path focuses on the fundamental tools and techniques needed to pursue a career in Big Data. This course includes: data processing with python, writing and reading SQL queries, transmitting data with MaxCompute, analyzing data with Quick BI, using Hive, Hadoop, and spark on E-MapReduce, and how to visualize data with data dashboards. Work through our course material, learn different aspects of the Big Data field, and get certified as a Big Data Professional!

Oct 26th 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.

Oct 26th 2026
5-12 Weeks
Data Science Ethics (Coursera) Coursera
University of Michigan

Data Science Ethics (Coursera)

What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values.

Oct 19th 2026
4 Weeks
A Scientific Approach to Innovation Management (Coursera) Coursera
Università Bocconi

A Scientific Approach to Innovation Management (Coursera)

How can innovators understand if their idea is worth developing and pursuing? In this course, we lay out a systematic process to make strategic decisions about innovative product or services that will help entrepreneurs, managers and innovators to avoid common pitfalls. We teach students to assess the feasibility of an innovative idea through problem-framing techniques and rigorous data analysis labelled ‘a scientific approach’.

Oct 19th 2026
5-12 Weeks
Gender Foundations in Health Data: A Data for Health Course (Coursera) Coursera
Johns Hopkins University

Gender Foundations in Health Data: A Data for Health Course (Coursera)

Welcome to Gender Foundations in Health Data: A Data for Health course. This course was developed from an online seminar series of the same name, that was hosted by Johns Hopkins University Bloomberg School of Health in 2021-22. The course instructors are Drs. Michelle Kaufman and Tahilin Sanchez Karver. This course will raise learners' awareness of the necessity of utilizing a gender lens in global public health data, policy, and practice, feature how-tos and key examples of integration of gender in data collection, analysis, and use from Data for Health partners.

Oct 26th 2026
1 Week
Machine Learning in Healthcare: Fundamentals & Applications (Coursera) Coursera
Northeastern University

Machine Learning in Healthcare: Fundamentals & Applications (Coursera)

Examines data mining perspectives and methods in a healthcare context. Introduces the theoretical foundations for major data mining methods and studies how to select and use the appropriate data mining method and the major advantages for each. Students are exposed to contemporary data mining software applications and basic programming skills. Focuses on solving real-world problems, which require data cleaning, data transformation, and data modeling.

Oct 26th 2026
4 Weeks
Using Databases with Python (Coursera) Coursera
University of Michigan

Using Databases with Python (Coursera)

This course will introduce students to the basics of the Structured Query Language (SQL) as well as basic database design for storing data as part of a multi-step data gathering, analysis, and processing effort. The course will use SQLite3 as its database. We will also build web crawlers and multi-step data gathering and visualization processes. We will use the D3.js library to do basic data visualization.

Oct 19th 2026
5-12 Weeks
Data Science for Business Innovation (Coursera) Coursera
Politecnico di Milano,EIT Digital

Data Science for Business Innovation (Coursera)

The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues.

Oct 19th 2026
4 Weeks