Heat Map

As data sets become larger, Heat Maps have become a critical tool in data visualization for data engineers and scientists - specifically (not a complete list):

• Visualizing Complex Data: Heat maps are great for visualizing large datasets by depicting the density of values in a matrix or grid format. This makes it easier to understand complex data patterns that might be difficult to see in raw, numerical data.
• Identifying Correlations: Heat maps can help identify if and where correlations exist between different variables.
• Highlighting Extremes: Heat maps use color gradients to represent data values. This allows for quick identification of high and low extremes in your data set.
• Spatial Analysis: Geographic heat maps can show the geographic distribution of data..
• Simplicity: Heat maps simplify complex statistical analyses into understandable graphics.
• Comparability: By placing different heat maps side by side, one can compare different data sets effectively. This is useful in A/B testing, marketing campaign analysis, etc.

Adding Heat Map Graphs to Dashboards is now common in most software packages (i.e. Excel, Tableau, etc.).

Please confirm if Heat Maps are on the 2024 Product Feature roadmap.