Scatter Plots for Correlation Analysis
Identify relationships between two metrics with Scatter Plots. Spot correlations, clusters, and outliers in your data.
Scatter Plots are the primary tool for correlation analysis. By plotting two numeric variables against each other, they reveal patterns, clusters, and outliers that are invisible in standard tables. Whether identifying the relationship between Ad Spend and Revenue or Height and Weight, Scatter Plots are essential for statistical discovery.
Edilitics makes advanced statistical plotting accessible via a point-and-click interface, capable of handling large governed datasets directly in the browser.
When to Use a Scatter Plot
| Use Case | Why This Chart Works |
|---|---|
| Corellation Analysis | Does Metric A increase when Metric B increases? (Positive Correlation). |
| Outlier Detection | Spot data points that defy the trend (e.g., High Spend but Low Revenue). |
| cluster Identification | See natural groupings of data (e.g., distinct customer segments). |
| Performance Matrix | Plot Satisfaction vs. Loyalty to map customers into quadrants. |
Chart Configuration in Edilitics
Inputs Required
| Data Type | Required Count | Description |
|---|---|---|
| Dimensions (Columns) | 1 | Categorical field to identify/group points (Symbol Detail). |
| Metrics (Rows) | 2 | Two numerical values: X-Axis position and Y-Axis position. |
How to Configure a Scatter Plot
- Select "Scatter Plot" from the Chart Library.
- Assign Axes:
- Drag your independent metric to X-Axis.
- Drag your dependent metric to Y-Axis.
- Define Granularity:
- Drag your category field to Symbol/Detail. Each unique value becomes a dot.
- Enhance (Optional):
- Color: Drag a field to color dots by category (e.g.,
Region). - Size: Drag a metric to size dots (creates a Bubble Chart).
- Color: Drag a field to color dots by category (e.g.,
Feature Highlights
Large Data Handling
- Canvas-based rendering ensures the chart remains smooth and responsive even with thousands of data points.
Data Zoom
- Enable the Data Zoom slider to allow users to focus on specific dense clusters of data without losing the overall context.
Rich Tooltips
- Tooltips display X, Y, and group details, helping you identify specific outliers (e.g., "Which specific store had high spend but low sales?").
Best Practices for Scatter Plots
| Practice | Why It Matters |
|---|---|
| Don't Overplot | If you have 100,000 points, they will overlap; use filtering or sampling to keep it readable. |
| Use Opacity | Set point opacity to 50-70% so that overlapping points create a darker area, indicating density. |
| Log Scales | If data spans several orders of magnitude, switch axes to Logarithmic scale to see patterns better. |
| Contextual Color | Use color to separate distinct groups (e.g., Male vs Female, Domestic vs International). |
How Edilitics Is Different
Unlike standard BI visualizers that often choke on high-volume scatter plots, Edilitics is optimized for performance:
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High-Volume Rendering: Plot detailed transaction-level or entity-level data without down-sampling or lag.
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Canvas-Based Engine: Thousands of points render smoothly using optimized canvas rendering.
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Drill-Down Capable: Click on any point to filter the entire dashboard to that specific outlier for immediate investigation.
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Governed Consistency: Your X and Y metrics are validated from the same governed dataset, ensuring accurate correlation analysis.
This lets you move beyond "averages" and see the true distribution of your business metrics.
Scatter Plots turn statistics into intuition. With Edilitics, you can explore the real distribution and relationship of your data without performance bottlenecks.
Need help? Email support@edilitics.com with your workspace, job ID, and context. We reply within one business day.
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