Dates
Wednesday 26 – Friday 28 November 2025 (3 DAYS ONLINE)
Fee structure
Students
600 NZD
Everyone else
1,200 NZD
Enrol
We are not yet open for enrolments, but watch this space, and please email nzssncourses@auckland.ac.nz for more information on courses and to join our mailing list.
Course outline
This practical online workshop introduces you to Microsoft Power BI, giving you the skills to turn raw data into clear, shareable insights. Over three half-day sessions, you will learn how to prepare, analyse, and present your data in an accessible and engaging way.
We will focus on approaches that are free to use, including browser-based options, so that participants can get started without needing a paid licence.
Who should attend?
This course is suitable for anyone new to Power BI who wants practical skills in presenting and exploring data. No prior experience with Power BI is required.
How does it work?
- Live, instructor-led online sessions delivered over three half-days
- Focus on using accessible, free Power BI options
- Hands-on exercises with real data examples
- Time for questions and discussion throughout.
Day one
- Introduction and getting started
- Understanding what Power BI is and how it can support data work
- Navigating the Power BI interface (browser and desktop versions)
- Connecting to common data sources such as Excel and CSV files
- Cleaning and transforming data with Power Query.
Day two
- Building effective visualisations
- Creating clear and interactive charts and tables
- Using filters, slicers, and drill-downs to explore data
- Designing straightforward, easy-to-use dashboards
- Options for sharing and publishing reports.
Day three
- Working with models and advanced features
- Understanding the relational data model in Power BI
- Creating relationships between tables to build richer analyses
- An introduction to Data Analysis Expressions (DAX) for custom calculations
- Best-practice tips for clear and effective design
- A look at some of Power BI’s built-in AI features, such as automated insights and natural-language Q&A.
If you want any further advice on whether this course is right for you, please email nzssncourses@auckland.ac.nz and we will put you in touch with the instructor.
Instructor
Daniel Fryer is an award-winning Honorary Lecturer and Associate Fellow of the Higher Education Academy of La Trobe University in Melbourne. He is a Senior Data Scientist specialising in Data Infrastructure at the Social Research Centre, technical sub-editor for the Australian & New Zealand Journal of Statistics, and Executive Privacy Officer for the Statistical Society of Australia, for which he also built the longitudinal member database.
Danny completed his PhD at the University of Queensland, applying coalitional game theory in machine learning.