This project is from Muhammad Tamimul Huda, which was awarded the Most Voted Award in the 2025 Quick BI Global Data Visualization Hackathon.
This project is an interactive dashboard designed to analyze and visualize global manufacturing production trends. Using the Production Index as a core metric, the dashboard provides a comprehensive overview of the manufacturing landscape by comparing the performance of various countries and industrial sectors over time. The main goal is to offer a clear, data-driven perspective on global economic activity, highlighting key players and dominant sectors in the manufacturing world.
🔗 Explore the project here
The main value of this project is its ability to transform complex economic data into actionable insights for decision-makers. For economists, investors, and policymakers, this dashboard serves as a powerful tool to identify top-performing countries and high-growth manufacturing sectors, assess economic stability by analyzing production consistency and growth volatility, and understand a country's industrial structure and its share in the global market.
The analysis was conducted using global manufacturing production index data. In the data preparation phase, key metrics were calculated, including Year-over-Year (YoY) growth and monthly growth volatility. In Quick BI, I developed a multi-faceted visualization approach. This includes time-series line charts, bar charts for comparisons, pie charts for production share, and a scatter plot for a strategic quadrant analysis.
One of the key highlights is the Sector Performance Quadrant analysis. This visualization distinctively maps out sectors into four categories (e.g., High Growth-High Volatility, High Growth-Low Volatility, etc.), revealing not just the top performers but also their risk profiles. For instance, we could identify emerging sectors that show rapid growth but are highly volatile, versus established sectors that are stable but have slower growth.
Another significant finding is the ability to directly compare the industrial structure of different economic powerhouses, showcasing which sectors dominate each country's manufacturing output and highlighting their strategic economic focus.
As a solo participant, I would describe myself as a curious, self-motivated learner. I entered this hackathon not with a formal background in data, but with a strong interest in how visual stories can be uncovered from complex numbers. This project was a personal challenge to learn and grow, and I am proud to have discovered meaningful insights through the process.
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