Introduction to Power BI
Explore, analyze, and visualize data using Power BI to make data-driven business decisions
Technologies & tools covered
Who is this bootcamp for?
Business analysts & executives
Learn how to build dashboards, track KPIs, and make data-driven decisions using real business datasets and Power BI's advanced features.
Finance, HR & operations teams
If you work with reports, metrics, or performance dashboards, Power BI helps you automate reporting and uncover trends faster than Excel ever could.
Entrepreneurs & freelancers
Master Power BI to offer analytics services, streamline business reporting, and position yourself as the go-to data storyteller in your space.
Meet the instructors
Learn from practitioners who build and deploy AI systems at scale
Curriculum
5 modules covering the full spectrum of theory and practice
Getting started with Power BI
Microsoft Power BI is a business intelligence tool that connects to various data sources and creates interactive visualizations to help you uncover insights. Whether your data comes from Excel, CSV files, or cloud and on-premises databases, Power BI lets you connect, transform, model, and visualize data easily.
What you'll learn
- Understand what Power BI is and its business value
- Install and navigate Power BI Desktop
- Identify key components and regional settings
- Learn core features and the Power BI workflow
Shaping data with Power BI Desktop
Power BI Desktop connects to multiple data sources through built-in connectors. Power Query, its data transformation engine, enables you to clean, reshape, and prepare data using an intuitive interface.
What you'll learn
- Identify different data connectors
- Connect to sources such as Excel, CSV, and PBIDS
- Assess data using Column Quality, Distribution, and Profile
- Apply basic transformations, handle nulls and errors, adjust data types
- Create Index, Conditional, and Example-based columns
- Group and aggregate data; Pivot and unpivot tables
- Merge and append queries using Power Query Editor
Creating a data model
Data modeling involves organizing data from multiple sources and defining relationships between tables to create a unified model. In Power BI Desktop, this allows you to build dynamic visuals and reports. A well-designed model simplifies data and improves report performance. You will also learn how to use the star schema and create calculated columns and measures using DAX (Data Analysis Expressions).
What you'll learn
- Define and create a data model
- Build and manage relationships between tables
- Understand relationship cardinality
Analyzing data using Data Analysis Expressions (DAX)
Data Analysis Expressions (DAX) is the formula language in Power BI, used for calculations and data analysis. It helps you create measures, columns, and tables for advanced reporting.
What you'll learn
- Create DAX tables, columns, and measures
- Use operators and mathematical functions
- Apply date, time, and text functions
- Use CALCULATE and FILTER functions for dynamic results
Data visualization
Power BI makes it easy to create insightful reports with rich visualizations that help you explore data and make informed decisions.
What you'll learn
- Explore built-in visual types and their applications
- Create visuals such as bar charts, line charts, hierarchy charts, Sankey diagrams
- Use filters, slicers, and drill-through features for deeper analysis
Earn a verified certificate
Earn a verified certificate and take your next career step with credibility.
We accept tuition benefits
Many employers and organizations offer tuition assistance or professional development budgets that can be applied to our programs. This means you may be eligible to attend the bootcamp for FREE.
Not sure? fill out the form so we can help.
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Reserve your spot
Explore, analyze, and visualize data using Power BI Desktop to make data-driven business decisions.
- Introduction to Power BI bootcampOnline
Available on request
What our alumni say
"As a leader of a BI organization, I came to the Bootcamp to learn as much as I could about predictive analytics. The week was intense, but it far exceeded my expectations. I learned the processes; I learned the theory; and I gained lots of hands on practice. This course gave me the knowledge and the the tool experience to bring predictive analytics back to my company - Jim Hill attended Data Science and Data Engineering Bootcamp."
A word from our alumni
Real stories from professionals who turned learning into lasting career growth
Frequently asked questions
- Is this program publicly available?
- This program is currently offered as private training for teams and enterprises. You can schedule a call with our advisors to discuss availability, group pricing, and a format tailored to your organization.
- Is the program full-time or part-time, and in-person or online?
- The format is flexible and can be tailored to your team's needs. It is typically conducted online over five days with around 15 hours of material. Contact us to discuss scheduling options for your group.
- What is the cost and are discounts available?
- Pricing depends on group size and format. Schedule a call with our advisors to discuss a package that works for your organization.
- How do I access the learning portal?
- Once you are registered for the program, you will receive a few emails from us. One of those emails will contain steps to create your learning portal account and access the program content.
- What is the transfer policy?
- Transfers are allowed once with no penalty. Transfers requested more than once will incur a $200 processing fee.
- What is the refund policy?
- If, for any reason, you decide to cancel, we will gladly refund your registration fee in full if you notify us at least five business days before the start of the training. We can also transfer your registration to another cohort if preferred. However, refunds cannot be processed if you have transferred to a different cohort after registration. Additionally, once you have been added to the learning platform and have accessed the course materials, we are unable to issue a refund, as digital content access is considered program participation.




















