In dense datasets, important patterns often remain hidden due to overlapping points.
Traditional scatter plots struggle when thousands of data points compete for space, masking trends and creating visual noise.
Hexbin charts address this challenge by grouping overlapping points into hexagonal bins, making concentration and distribution easier to see.
Use Case: Mapping Ecommerce Order Volume by Location
This example compares a scatter plot with a hexbin chart to illustrate ecommerce order volume across New York City neighborhoods.
Key observations:
• Urban centers show concentrated activity and high order flow
• Peripheral zones reflect sparse demand patterns
• The hexbin view highlights patterns that support spatial decisions such as delivery planning, store placement, and hotspot identification
At Perceptive Analytics our mission is “to enable businesses to unlock value in data.” For over 20 years, we’ve partnered with more than 100 clients—from Fortune 500 companies to mid-sized firms—to solve complex data analytics challenges. Our services include Advanced Analytics, Generative AI, and Business Intelligence (Tableau, Power BI and Looker) turning data into strategic insight. We would love to talk to you. Do reach out to us.
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