Fields suitable for the selected heatmap type
- Requirement
- Required
- Example
- Weekday, Hour, Ticket Count
- Purpose
- Needed for the core workflow
Upload structured data and choose the row, column, value, and aggregation fields to create a readable matrix or correlation heatmap.
Supports structured .csv and .xlsx files. Public examples use synthetic data. Review VizMint's current privacy and retention policy before uploading sensitive information.
Use the fixed preview below to switch between the source spreadsheet and a dashboard sample. Open the full demo in a new tab for every KPI and chart.
CSV Heatmap Generator
Interactive preview from the sample support heatmap dataset
Switch preview
Total Records
56
rows in sample
Total Total Resolution Minutes
308,589
sum of Total Resolution Minutes
Total Total First Response Minutes
65,649
sum of Total First Response Minutes
Bin width 1,000 · 56 observations
Full dashboard with all KPI details and 6 charts is on the demo page.
Open full demoThe sample contains 56 matrix cells across 7 weekdays and 4 issue types. Charts and KPI cards are generated from the same JSON dataset.
Sample totals: 1,927 tickets, 560 valid numeric cells, and 0 missing values — with aggregation published beside the colour grid.
Create a heatmap only after confirming the two dimensions, aggregation, missing-value treatment, and scale.
A chart generator should help the user choose a valid visual, not simply draw whatever was requested. Data type, aggregation, binning, scale, and missing values determine whether the chart is honest.
The support sample maps issue type by weekday using 1,927 tickets across 56 cells and publishes the aggregation table beside the colour grid.
The workflow is designed around explained chart choice, visible settings, and a supporting data table.
This workflow works best when users can explicitly select the heatmap type, dimensions, numeric value, and aggregation. The workflow distinguishes matrix, category-by-period, and correlation heatmaps.
The result brings the most important metrics, trends, and exceptions into one view, while keeping the supporting records available for review.
Follow the same dataset from source rows to the generated dashboard preview. The spreadsheet table, KPI cards, and charts all come from one JSON sample, so every visible result can be checked against the source.
The source preview highlights the exact columns and representative rows used by the workflow.
| Weekday | Issue Type | Channel | Agent Team | Total Resolution Minutes |
|---|---|---|---|---|
| Monday | Login & Access | Chat | Tier 1 | 4,582 |
| Monday | Billing | Billing Desk | 7,421 | |
| Monday | Orders | Phone | Tier 1 | 10,176 |
| Monday | Technical | Web Form | Billing Desk | 6,536 |
| Monday | Login & Access | Chat | Tier 1 | 8,304 |
The finished output includes the KPI cards, charts, tables, and report views described below.
Bin width 1,000 · 56 observations
VizMint works best when every column has one clear heading and each row represents one consistent record. Fields that are not available should not be invented; dependent outputs should be hidden or clearly marked as unavailable.
| Column | Requirement | Example | Purpose |
|---|---|---|---|
| Fields suitable for the selected heatmap type | Required | Weekday, Hour, Ticket Count | Needed for the core workflow |
| Row Dimension | Recommended | Issue Type | Adds an important comparison or breakdown |
| Column Dimension | Recommended | Weekday | Adds an important comparison or breakdown |
| Numeric Value | Recommended | 29 | Adds an important comparison or breakdown |
| Date | Optional | 2026-06-01 | Adds detail when present |
| Category | Optional | Billing | Adds detail when present |
| Segment | Optional | Chat | Adds detail when present |
| Label | Optional | HM-001 | Adds detail when present |
Count of distinct row-dimension values used to build the heatmap matrix.
Count of distinct column-dimension values used across the colour grid.
Number of numeric values available for aggregation after exclusions.
Count of blank or invalid cells that affect colour intensity and aggregation.
The confirmed method used to combine duplicate row-column combinations, such as sum or average.
| Chart or Output | Required Fields | Business Question |
|---|---|---|
| Matrix Heatmap | Row dimension, column dimension, numeric value | Which combinations have the highest values? |
| Correlation Heatmap | Multiple valid numeric columns | Which variables move together? |
| Category-by-Period Heatmap | Category, date or period, numeric value | How does activity vary by day and hour? |
| Pivot-Style Heatmap | Two dimensions and an aggregation | Where are category or supplier concentrations? |
Upload the workflow-specific sample or a user file.
Select the correct worksheet when the workbook contains multiple sheets.
Confirm the detected header row and field mapping.
Review the data preview, exclusions, and validation warnings.
Generate the dashboard, chart, report, presentation, or answer.
Review KPI values, calculations, charts, and source traceability.
Save, share, or export using capabilities available on the active plan.
| Metric | Formula or Method | Required Fields | Important Rule |
|---|---|---|---|
| Aggregation | Sum, average, count, minimum, or maximum | Selected numeric value and dimensions | The user should select or confirm the aggregation. |
| Correlation | Selected numeric correlation method | Two or more valid numeric columns | Do not imply causation or use mixed non-numeric fields. |
| Problem | Recommended Fix |
|---|---|
| Non-numeric values | Document the rule, standardize the source data, and validate the corrected result before generation. |
| Too many categories | Document the rule, standardize the source data, and validate the corrected result before generation. |
| Duplicate cells without aggregation | Use a stable identifier, review repeated rows, and remove or reconcile duplicates before calculation. |
| Sparse matrices | Document the rule, standardize the source data, and validate the corrected result before generation. |
| Mixed units | Document the rule, standardize the source data, and validate the corrected result before generation. |
Available sharing and export options depend on the live VizMint plan. Publish only capabilities confirmed in production, such as saving the analysis, downloading images or PDF files, exporting PowerPoint, creating private links, refreshing a saved report, or removing branding on eligible plans.
Do not hardcode plan limits, file-size limits, privacy promises, or export features until product and billing owners confirm them.
VizMint analyzes exports; it does not replace the accounting, CRM, help-desk, HR, warehouse, advertising, or project-management system that produced them.
Upload a structured CSV or Excel file to generate the supported metrics, charts, and comparisons for this workflow.