Intermediate Data Analytics on Microsoft Power BI

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Course Description

In today’s highly competitive and data-driven business environment, business intelligence (BI) is crucial for informed decision-making. As organizations generate vast amounts of data through digital tools and increased storage capabilities, the need for powerful BI solutions to summarize, visualize, and extract meaningful insights becomes increasingly critical. Microsoft Power BI has emerged as an indispensable platform for transforming raw data into actionable insights and intelligence to support decision-making.

Building on the foundational skills introduced in the beginner-level course, this intermediate course is designed to deepen learners’ proficiency with Power BI. Over six weeks and four comprehensive modules, participants will gain practical experience working with real-world data and realistic case studies, focusing on both Power BI Desktop and Power BI Service. The course covers advanced topics such as enhancing data models with DAX, securing reports with row-level security (RLS), transforming data using the Power Query M language, and turning business questions into charts and dashboards. Learners will also explore the integration of AI features for text analytics, interactive report design with bookmarks and filters, and effective report sharing through Power BI Service.

By the end of the course, learners will be equipped to build robust data models, create visually compelling reports and dashboards, and tell meaningful data stories – making them trusted partners in business decision-making.

Learning Outcomes

On successful completion of this course, learners will be able to:

1.       Apply the Extract, Transform, Load (ETL) process in Power BI Desktop using data from various sources, including flat files, web content, folders, and databases.

2.       Clean, transform, and shape data using Power Query and the M language to prepare it for analysis.

3.       Enhance data models using Data Analysis Expressions (DAX) to create calculated columns and measures.

4.       Design and customize reports in Power BI Desktop by integrating interactive elements such as buttons, shapes, text boxes, images, filters, and Q&A features.

5.       Create and apply bookmarks to enable storytelling and improve report navigation.

6.       Implement row-level security (RLS) to control access to data within Power BI reports.

7.       Build and publish interactive reports and dashboards in Power BI Service.

8.       Collaborate by sharing reports and dashboards securely with colleagues and stakeholders.

  • Course Outline

    Module 1: Connecting to External Sources in PowerBI Desktop

    Lesson 1: Understanding the Extract, Transform, Load (ETL) Framework

    Lesson 2: Extracting Data from Flat Files

    Lesson 3: Connecting to Web Sources

    Lesson 4: Setting up Folder Connection

    Lesson 5: Extracting Data from Databases

    Module 2: Cleaning, Transforming and Shaping Data in Power Query

    Lesson 1: Transforming Data with Cleaning Operations

    Lesson 2: Shaping Data with Power Query M Language

    Lesson 3: Introduction to Text Analytics with Artificial Intelligence (AI) Features

    Module 3: Enhancing Reports in Power BI Desktop

    Lesson 1: Enhancing Data Models with DAX

    Lesson 2: Adding Elements (Text Box, Buttons, Shapes, Images) to a Report

    Lesson 3: Creating Bookmarks

    Lesson 4: Implementing Security and Access

    Lesson 5: Use Filters and Q&A in a Report

    Module 4: Creating Reports and Dashboards with Power BI Services

    Lesson 1: Importing Data into PowerBI Service

    Lesson 2: Creating Reports

    Lesson 3: Creating Bookmarks

    Lesson 4: Use Filters and Q&A in a Report

    Lesson 5: Sharing Reports with Colleagues and Others

    Learning Resources

    I. Recommended Books

    1.       Microsoft Power BI For Dummies, Jack Hyman (Author), 2022, John Wiley & Sons, Inc., Hoboken, New Jersey

    2.       Mastering Microsoft Power BI, Greg Deckler & Brett Powell, 2nd edition, June 2022, Packt Publishing

    3.       Storytelling with Data: A Data Visualization Guide for Business Professionals, by Cole Nussbaumer Knaflic (Author), Wiley

    4.       Business Analytics: Data Analysis & Decision Making, by S. Christian Albright (Author) and Wayne L. Winston (Author), 7th edition, Cengage

    5.       Excel Power Pivot & Power Query For Dummies, by Michael Alexander (Author), 2nd edition, Wiley

    6.       The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios, by Steve Wexler (Author), Jeffrey Shaffer (Author) and Andy Cotgreave (Author)

    II. Online Resources

    Occasionally, the instructor will share selected articles, videos, and links to other online resources, which will be sent by email or made available via Google Drive.

    Evaluation Modalities

    1.       Individual in-class assignment

    2.       Weekly Quizzes

    3.       Home assignments

    4.       Individual Capstone Project

    Equipment Requirements

    1.       Software

    a.       Windows 8.1 or later (Warning: Power BI Desktop does not work on Mac)

    b.       Power BI Desktop: learners will learn how to install it on their computer during the course

    c.       Power BI Service / Power BI Pro (free or licensed version)

    2.       Hardware:

    a.       2 GB of RAM (minimum)

    b.       CPU: 1 GHZ or faster (64-bit processor).

    • Ability to speak, understand and write in English (CLB6).

    • Beginner level knowledge of Microsoft Excel is required.

    • Completion of Introduction on MS PowerBI course

  • 1. Software

    • Windows 8.1 or later

    • Power BI Desktop: learners will learn how to install it on their computer during the course

    • Power BI Service / Power BI Pro (free or licensed version)

    2. Hardware:

    • 2 GB of RAM (minimum)

    • CPU: 1 GHZ or faster (64-bit processor).

    Please note that the PowerBI Desktop software does not work well on Mac computers

  • CAD $625

  • Waldo Beauséjour is a seasoned senior data analyst with over a decade of experience in the field of data analytics. His extensive expertise spans various sectors, including government, international development, research organizations, the private sector, and healthcare. Waldo holds a Master’s degree in applied economics, equipping him with a robust foundation in quantitative methods. His passion for education and teaching has driven him to serve as a college instructor in Canada, a dedicated tutor and graduate assistant in the USA, and a respected university professor in his home country. He firmly believes that a strong grasp of statistics empowers individuals to interpret data with confidence, thereby enhancing their capacity to extract valuable insights for informed decision-making. This conviction has led him to dedicate a significant portion of his professional journey to training professionals in the field of data analytics and equipping them with the necessary tools for effective data analysis.

  • Training Mode: Online

    Course length: 6 weeks, 30h

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