1. Opening Statement
For this Power BI Data Viz contest, my main motivation was to blend the passion for data analysis with excellence in UX (User Experience) and UI (User Interface). I interpreted the theme as the critical need to help future college students navigate the complex educational landscape and choose the best academy of magic in Fabricland.
The goal of my project, the Fabricland Academy Explorer, is to tell a clear story about cost-benefit, investment, starting salary, and evaluations, transforming raw data into a reliable and aesthetically pleasing decision guide. It is a tool designed to ensure every aspiring wizard makes the right choice.
2. Tools and Approach
The report was built using Power BI Desktop, leveraging the power of DAX for high-performance calculations. To elevate the user interface and visual appeal, I utilized custom HTML visuals. This technique allowed me to create rich, dynamic elements, ensuring that the dashboard's aesthetics and usability were perfectly aligned with modern design standards.
Functionality Highlights and Notable Techniques:
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Enhanced Navigation and Usability (Bookmarks): I strategically used Bookmarks to boost interactivity, allowing the user to:
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Open and close a side filter pane to refine analysis.
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Access a dedicated user support area.
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Toggle between chart views on the Overview page (switching between "General Overview" and "Cost and Return").
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Navigate through the different tabs of the User Guide.
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Custom Tooltips: I implemented custom tooltips that act as informative pop-ups throughout the report, ensuring users receive valuable context without shifting focus from the main visual.
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Advanced Features: The project includes logged-in user identification (adding a professional touch), intelligent adaptation of native visuals, dynamic insights within the report, and direct access to the Project Documentation for transparency.
3. Report Walkthrough
A. Overview (Academy Overview)
This page provides a high-level view of the Fabricland ecosystem. It displays key indicators, such as the Employability Rate (90%) and the Magic Score (an existing indicator summarizing overall quality). The "Cost and Return" sub-tab is vital, presenting the relationship between Monthly Investment (Tuition) and the Average Starting Salary, helping to identify academies with the best return.
B. Programs (Performance and Enrollment)
Allows analysis of performance and enrollment trends across all 34 programs, showing the Average Graduation Rate (91%), internship availability, and historical trends by academic level.
C. Comparison (Direct Comparative Analysis)
The heart of the tool. It enables side-by-side benchmarking between two institutions. Users can select two academies and compare 10 Key Metrics (Quality, Finance, etc.). The visual indicators (✓/❌) and the Oracle's Verdict facilitate the quick identification of which college offers the best value proposition.
D. Data Hub (Complete Catalog)
Serves as the central catalog, presenting a searchable table of programs, detailing categories, difficulty levels (Easy, Medium, Hard), and the Average Starting Salary, providing the necessary granularity for in-depth analysis.
4. Challenges and Lessons Learned
While development went smoothly, the main challenge was maintaining UI consistency, clarity, and elegance across a dashboard with so many advanced features (HTML, multiple bookmarks, tooltips). I invested significant time in the design phase to ensure the magical interface was intuitive, not confusing.
Future Improvement and Lesson: To take the project further, I would enhance the dynamic insights functionality so they could automatically analyze and write narrative reports about the comparison between the two colleges (on the Comparison page). This would increase the analytical value and personalization for the user.
5. Link to Contact
Thank you for reviewing my work on the 'Fabricland Academy Explorer'. I would love to hear your feedback and connect with other members of the Power BI community.
🔗Connect with me on LinkedIn: https://www.linkedin.com/in/nayara-hellen-data-analyst/
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