01 / The brief

The question

Build a clear Power BI dashboard that helps users explore LEGO sets, compare themes, understand price trends, and identify top-performing sets.

This project analyzes LEGO sets data using Power BI. It helps users understand total LEGO sets, average number of pieces, number of themes, average retail price, yearly growth, theme performance, set prices, minifigures, piece count distribution, and detailed set-level insights. The dashboard includes three report pages. The first page focuses on overview metrics, yearly growth, top themes, average price, and piece count distribution. The second page explores themes, most popular themes, most expensive themes, minifigures, and theme-level analysis. The third page provides detailed set analysis including top sets by pieces, age range distribution, top theme groups, minifigure counts, and price versus pieces.

Results & observations

  • The final dashboard gives a clear view of LEGO set growth, theme popularity, pricing patterns, minifigure distribution, piece count trends, and detailed set performance.
  • Users can quickly identify the most popular themes, most expensive themes, sets with the most pieces, and pricing relationships across LEGO sets.

Challenges

  • Combining set, theme, price, minifigure, piece count, and year data into one dashboard
  • Making LEGO theme performance easy to understand
  • Showing long-term LEGO growth clearly
  • Comparing set price and piece count trends
  • Designing simple visuals for detailed set exploration

Approach

  1. I cleaned and prepared the LEGO sets dataset.
  2. I created Power BI measures for total sets, average pieces, number of themes, average retail price, theme counts, and set-level performance.
  3. I designed dashboard pages for overview, thematic exploration, and detailed set analysis.
  4. I added visual comparisons by year, category, theme, sub-theme, piece count, minifigures, age range, and price.
Implementation details

Data Preparation

Cleaned and prepared the LEGO sets dataset for analysis.

Data Modeling

Created the Power BI data model for sets, themes, sub-themes, years, prices, pieces, and minifigures.

DAX Development

Built measures for total sets, average pieces, theme count, average retail price, set rankings, and growth trends.

Overview Dashboard

Designed the overview page with key metrics, yearly growth, theme rankings, price trends, and piece count distribution.

Theme Analysis

Created thematic exploration visuals for popular themes, expensive themes, minifigures, and category distribution.

Detailed Set Analysis

Built detailed set-level visuals for top sets, age range, theme groups, minifigures, and price versus pieces.

Explore the report

Select a screenshot for a larger view.