Course: Tableau Data Visualization and Business Intelligence
Learning Objectives: Understand heat maps, learn how to create them in Tableau, apply colors and sizes to measures, interpret patterns, customize formatting, and build an interactive heat map dashboard.
Course Link: JustAcademy Tableau Training
Demo Link: Register for a Tableau Course Demo
Official Tableau Reference: Build a Highlight Table or Heat Map
A heat map is a data visualization technique that uses colors to represent the magnitude, frequency, intensity, or distribution of values. In Tableau, a heat map can use both color and size to communicate information about measures across categories.
Heat maps make it easier to identify high values, low values, clusters, unusual results, and patterns in large datasets without examining every individual number.
For example, a business can use a heat map to compare sales across regions and product categories. Darker or more intense colors may indicate higher sales, while lighter colors may indicate lower sales, depending on the selected color palette.
| Region | Furniture Sales | Technology Sales | Office Supplies Sales |
|---|---|---|---|
| East | 85000 | 120000 | 65000 |
| West | 110000 | 145000 | 90000 |
| Central | 60000 | 95000 | 55000 |
| South | 75000 | 105000 | 70000 |
A heat map can convert this table into a grid of colored cells. A viewer can quickly identify that Technology sales are comparatively high in the West and comparatively low in the Central region.
Dimensions describe categories or groups. They generally determine the rows and columns of a heat map.
Examples include Region, Category, Sub-Category, Segment, Department, Month, Product Name, and Customer Type.
Measures are quantitative values that can be aggregated and analyzed. They are commonly used to control the color or size of marks.
Examples include Sales, Profit, Quantity, Discount, Revenue, Order Count, and Delivery Time.
The Rows shelf and Columns shelf organize dimensions into a grid. Each intersection represents a combination of category members for which Tableau displays a value.
The Marks card controls how the data appears. Its options include Color, Size, Label, Detail, and Tooltip. For a typical grid-based heat map, Square is a useful mark type.
The color legend explains the relationship between colors and measure values. Always ensure that the legend is visible and easy to understand.
In a heat map, size can represent an additional measure. For example, color can represent Profit while the size of each square represents Sales. This allows two measures to be compared in one view.
| Feature | Grid Heat Map | Highlight Table | Density Heat Map |
|---|---|---|---|
| Main purpose | Compare category combinations using color and size | Highlight values in a text table using color | Show concentrations of overlapping data points |
| Typical marks | Squares or other sized marks | Colored cells with optional text values | Density marks |
| Color represents | A measure such as Sales or Profit | A measure such as Sales or Profit | Relative concentration of marks |
| Size represents | Optionally, a second measure | Usually not the primary encoding | Kernel size can be adjusted |
| Common use | Sales by Region and Category | Profit values in a readable grid | Concentrations of geographic points or dense scatterplot data |
Important: A grid-based heat map and a density heat map are different visualizations in Tableau. The grid-based version compares measures across dimensions. A density heat map uses the Density mark type to reveal areas where many data points overlap.
Use Tableau's Sample - Superstore dataset. It commonly contains fields such as Region, Segment, Category, Sub-Category, Sales, Profit, Quantity, and Order Date.
Drag Segment from the Data pane to the Columns shelf. Tableau displays the available segment categories as column headers.
Drag Region to Rows. Then drag Sub-Category to Rows beside Region to create a more detailed grid.
The combination of Region and Sub-Category provides a way to compare products across different business regions.
On the Marks card, open the mark-type dropdown and select Square. Square marks make the individual cells easy to distinguish.
Drag Profit to Color on the Marks card. Tableau colors each mark according to the aggregated profit value, usually SUM(Profit) by default.
Higher and lower values will appear in different shades according to the chosen palette. The exact meaning of each color depends on the legend and color settings.
To make the visualization a more expressive heat map, drag Sales to Size on the Marks card. The size of each square will vary according to sales, while color continues to represent profit.
Click Size on the Marks card and move the slider until the marks are large enough to compare but do not overlap excessively or obscure neighboring cells.
Drag Profit or Sales to Label on the Marks card if users need to see exact values. If the grid contains many cells, displaying every number may make the visualization difficult to read.
Add a clear worksheet title, review the row and column headers, adjust cell spacing and borders, and confirm that the color legend accurately describes the displayed measure.
For detailed Tableau instructions, see Tableau's official heat map and highlight table guide.
Tableau's Show Me panel can help you select an appropriate visualization based on the fields selected in the Data pane.
Note: The available Show Me options depend on the fields selected and their data types. If the required visualization is not available, create the view manually using the Rows, Columns, and Marks shelves.
A sequential palette uses a progression of shades to represent low-to-high values. It is appropriate for values such as sales, order counts, revenue, or quantity when the primary goal is ranking magnitude.
Example: Light blue for lower sales and dark blue for higher sales.
A diverging palette uses two contrasting color directions around a meaningful center. It is especially useful for values that can be positive or negative, such as profit or variance from a target.
Example: One color family represents losses and another represents profits, with a neutral midpoint around zero.
Categorical palettes are most useful for distinguishing discrete groups. For a numerical heat map, a continuous sequential or diverging palette is generally more appropriate because it shows the magnitude of a measure.
A heat map can communicate two different measures at the same time. For example:
In this view, a large square indicates a high sales value relative to the other marks, while its color indicates the profit value. A large square with a loss-indicating color can reveal a product that generates substantial sales but performs poorly in profitability.
Do not assume that the largest mark is automatically the best performer. Interpret its size together with its color, tooltip, and legend.
A retail company wants to understand which product sub-categories perform well across different regions and customer segments. The company needs to identify high-sales areas, low-profit areas, and potential business risks.
| Tableau Area | Field or Setting | Purpose |
|---|---|---|
| Columns | Segment | Compare customer segments |
| Rows | Region, Sub-Category | Organize products by region |
| Marks type | Square | Create distinct grid cells |
| Color | SUM(Profit) | Show profitability |
| Size | SUM(Sales) | Show sales magnitude |
| Tooltip | Region, Sub-Category, Sales, Profit | Provide detailed information on hover |
Use the heat map to identify cells that deserve closer investigation. A large cell with a loss-indicating color may suggest high sales with low or negative profit. Before making a business decision, inspect the underlying values and consider factors such as discounts, product costs, returns, and order volume.
A density heat map is different from a grid heat map. It is useful when a view contains many overlapping marks and you want to identify areas where points are concentrated.
Density marks use color to show the relative concentration of overlapping points. They are useful for spatial analysis, crowded scatterplots, and other views with many marks.
Read more in Tableau's official guide to density marks.
Use a title that explains the measure and categories, such as Profit by Region, Product Sub-Category, and Customer Segment.
Use subtle borders to distinguish adjacent cells. Borders should provide structure without distracting from the data colors.
Resize rows and columns so that category labels remain readable and the grid does not feel overcrowded.
Include useful fields such as Region, Segment, Sub-Category, Sales, Profit, and Quantity. Tooltips help users explore precise values without displaying every number directly in the grid.
Sort categories in a logical order or by an important measure to make comparisons easier. For example, sorting sub-categories by profit can help users identify strong and weak performers more quickly.
Add filters such as Order Date, Region, Category, or Segment when users need to focus on a specific part of the data. In a dashboard, show only filters that serve a clear analytical purpose.
Format currency, percentages, and large numbers consistently. For example, use an appropriate currency format for Sales and Profit and avoid mixing different number formats within the same report.
A dashboard is most useful when the heat map answers a specific question and works alongside related views rather than displaying unrelated information.
| Problem | Possible Cause | Solution |
|---|---|---|
| Heat map displays text instead of colored squares | Mark type or Color configuration is not suitable | Select Square and drag a measure to Color. |
| All cells appear almost the same color | Values are similar or the color range is not visually effective | Review the range and choose a more suitable palette. |
| Squares are too small | Size setting is too low or the view has many marks | Adjust the Size slider and available worksheet space. |
| Labels overlap | Too many labels are displayed | Remove unnecessary labels and rely on tooltips. |
| Negative profit is difficult to identify | Palette does not distinguish positive and negative values clearly | Use a diverging palette centered around zero when appropriate. |
| Values seem unusually large | Measure is aggregated as SUM instead of the intended aggregation | Verify whether SUM, AVG, COUNT, or another aggregation matches the question. |
| Some categories are missing | Filters, null values, or data relationships may affect the view | Review filters, source data, joins, relationships, and null handling. |
| Heat map is difficult to read | Too many categories or overly complex formatting | Filter the view, simplify dimensions, and use a clear title and legend. |
Answer: A heat map is a visualization that uses color, and often size, to represent measure values across categories. It helps users identify patterns, high and low values, and unusual combinations.
Answer: A highlight table is a text table enhanced with color. A grid heat map can use both color and size to encode measures, allowing viewers to compare two measures simultaneously.
Answer: Square is commonly used because it creates clear, separate cells. The appropriate mark type can vary depending on the analytical goal.
Answer: The Color shelf controls mark colors. Placing a continuous measure on Color maps its values to a color range.
Answer: The Size shelf controls mark size. A continuous measure can be used to vary square sizes, making it possible to compare a second measure.
Answer: Use a diverging palette when values vary around a meaningful midpoint, such as zero profit, positive versus negative variance, or above versus below a target.
Answer: Yes. Add a measure to Label on the Marks card, or configure a tooltip. However, displaying labels in every cell may make a large heat map difficult to read.
Answer: A density heat map uses density marks to highlight areas where many data points overlap. It is commonly used for geographic concentrations and dense point-based views.
Answer: Tableau commonly aggregates measures, such as using SUM by default. The selected aggregation may not match the intended analysis. Check whether SUM, AVG, COUNT, or another aggregation is appropriate.
Answer: Use a meaningful title, a suitable palette, readable row and column labels, a clear legend, useful tooltips, subtle borders, and only the filters and labels needed for the analysis.
Creating heat maps in Tableau is an effective way to compare measures across categories and identify patterns in business data. By placing dimensions on Rows and Columns, selecting Square marks, using Color for a measure, and optionally using Size for another measure, you can build a clear and informative visualization. Appropriate color palettes, correct aggregation, readable labels, useful tooltips, and thoughtful dashboard design make the analysis more accurate and actionable.
For further learning, visit JustAcademy Tableau Training or Register for a Tableau Course Demo.
