The Dashboard Builder has more than 50 built in charts and widget items for you to use. You can easily pick the items and insert them into your dashboards.
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In this article, we will focus on the following special chart widgets:
- Combination chart
- Parallel coordinates plot
- Bubble chart
- Strip plot
- Radar chart (Spider chart)
- Pyramid chart
- Funnel chart
- Alluvial diagram
- Sankey diagram
- Box plot
- Heat table
- Word cloud chart
1. Combination chart
The combination chart is a data visualization that combines the features of the bar chart, line chart, scatter plot, and area chart. The combination chart displays the data using a number of bars, lines, plots, and/or areas, each of which represent a particular category. A combination of different visuals in the same visualization can be useful when comparing values in different categories, since the combination gives a clear view of which category is higher or lower. An example of this can be seen when using the combination chart to compare the sales goals with the actual sales for different time periods.
Use cases:
- Comparing sales revenue (bar) with profit margins (line).
- Displaying temperature (line) and precipitation (bar) on the same chart.
Common data in assessments:
• Employee performance (bars) and satisfaction scores (lines) over time.
On the combination chart, you can drag multiple data points as "measures".
In the settings, you can select the measures and the visualization mode.
2. Parallel coordinates plot
A parallel coordinates plot visualizes multi-dimensional data using parallel axes.Each variable gets it’s own axis where data points are plotted. Data points are then connected with lines as such it’s easy to read the graph and discover trends or dependencies.
If you have data that you would like to analyze based on multiple variables and potentially discover some dependencies - parallel coordinates chart would work perfectly for it!
Use cases:
- Comparing multiple attributes of survey respondents.
- Analyzing complex datasets with multiple variables.
Common data in assessments:
- Attributes like skill levels, satisfaction, and engagement across departments.
3. Bubble chart
The Bubble chart is a playful way to display how many values you have per category. The higher the value, the bigger the bubble so you can see your biggest categories in a glimpse. Which you can also visually group together by color.
Use cases:
- Visualizing market share, sales, and growth rate.
- Plotting survey responses by importance, satisfaction, and response count.
Common data in assessments:
- Importance of skills (X), proficiency levels (Y), and number of respondents (bubble size).
4. Strip plot
A strip plot displays individual data points along a single axis to show distribution.
Use cases:
- Highlighting individual survey responses.
- Comparing responses across different categories.
Common data in assessments:
- Individual employee satisfaction scores across departments.
5. Radar chart (spider chart)
Radar chart (sometimes also called web, radial or spider chart) is widely used for multivariable comparison. It allows you to visually represent data for a high number of variables in a neat way.
When visualizing data on the radar chart each category gets its own axes. A value for each category is then plotted on these axes. Finally, those data points are simply joined as such you see intersections between categories.
Use cases:
- Comparing performance across different skills.
- Visualizing survey results on various attributes.
Common data in assessments:
- Employee competencies across multiple skills.
6. Pyramid chart
A pyramid chart visualizes hierarchical data with each level representing a proportion of the whole. This chart is commonly used to visualize demographics data that is usually represented by two categories - female and male and can be grouped by age, for example.
However, it can be perfectly used to compare any other categories too.
In essence, pyramid chart contains of two bar charts that are mirrored. So it is easy to compare categories between each other.
Use cases:
- Displaying sales funnel stages.
- Showing organizational hierarchy.
Common data in assessments:
- Hierarchical levels of employee engagement or development stages.
There are two labels on this chart:
- Bins: Columns with data types ‘hierarchy’ and ‘date time’ are a perfect fit for this label.The data added to this label defines how many levels - or bins - will appear in your pyramid chart. In this example, we use year level as such the amounts from the same year will be aggregated.
- Measure: Columns with data type ‘numeric’ or ‘hierarchy’ work best for this slot. The measure label determines the numeric value of a bin. The higher the value, the longer the bar would be. Different aggregations can be set to execute different calculations, e.g. the average.
7. Funnel chart
A funnel chart represents data in stages, with each stage decreasing in size to indicate progression. By default, the difference in stage values compared to the total of data is translated in the different widths of the parts. Meaning, the more items in one stage, the wider the part. This gives you the opportunity to notice a bottleneck stage at a glance for example.
Use cases:
- Visualizing sales or recruitment funnels.
- Showing step-by-step survey completion rates.
Common data in assessments:
- Stages of training program completion.
There are two labels on this chart:
- Category: Columns with data types ‘hierarchy’ and ‘date time’ are a perfect fit for this label. The data added to this label defines how many stages - or parts - will appear, as such five different stages will divide the funnel in five parts. The measures from the same stage will be aggregated into one part.
- Measure: The measure label defines the numeric value of a stage. By default, the higher the value, the wider the part. Different aggregations can be set in order to be able to execute different calculations, e.g. the average.
8. Alluvial diagram
An alluvial diagram visualizes the flow of material, energy, cost, or measurable resources over a specific time frame. Its name derives from the natural alluvial fans, reflecting the diagram’s appearance and function.
Structure:
- Dimensions are assigned to parallel vertical axes.
- Measures are represented by bars on either axis.
- Bar height indicates category size, while flow height shows the size of components shared between categories.
Use cases:
- Analyzing migration patterns of survey responses.
- Showing changes in employee roles or departments.
Common data in assessments:
- Employee transitions between different job roles.
9. Sankey diagram
A Sankey chart visualizes flows and traffic amounts, with flow width proportional to quantity. Like a tree, it branches into multiple subcategories, each further divided. The chart highlights the size of connections between subcategories, making it ideal for sum aggregations. Sankey charts are effective for showing conditional flows and the magnitude of relationships between various categories.
Use cases:
- Tracking the flow of respondents through different survey sections.
- Visualizing resource allocation in a project.
Common data in assessments:
- Movement of employees between training programs or departments.
10. Box plot
A box plot summarizes interval-scale data, often used in exploratory data analysis. It visually displays the distribution shape, central value, and variability by dividing data into four equal parts (quartiles). The median, minimum, and maximum values are easily recognizable.
Advantages include the ability to quickly spot the variable’s spread and outliers, and it doesn’t require much space, making it ideal for comparing multiple categories. Use cases include visualizing sensor data, operational data, and sales data, providing a clear overview at a glance.
Use cases:
- Comparing scores across different groups.
- Highlighting data variability.
Common data in assessments:
- Distribution of employee performance scores.
You can adjust the colors in the widget setting to make your chart data more clear.
11. Heat table
A heat table graphically represents data to visualize the volume of events within a dataset, directing viewers to significant areas where values of a matrix are represented as colors. Magnitudes are displayed in a matrix of fixed cell sizes, with rows and columns corresponding to discrete phenomena and categories. The goal is to identify clusters or outliers, providing a clear and immediate understanding of data distribution and concentration.
Use cases:
- Visualizing response frequency in surveys.
- Highlighting areas of concern or high performance.
Common data in assessments:
- Frequency of different responses to survey questions.
X-axis and Y-axis
Columns with the ‘hierarchy’ data type are ideal for these slots. You can also use specific date levels, such as year or month, or numeric data. Depending on your use case, consider enabling or disabling binning in the data slot settings when using numeric data.
The data in these slots determines the number of boxes (combinations of categories) that will appear. For instance, if your X-axis has 4 unique values and your Y-axis has 5, you will see a total of 4 x 5 boxes. Measures from each category combination are aggregated into these boxes.
Ensure not to overload the chart with too many categories, as it may become cluttered and hard to analyze.
Measure
Columns with a ‘numeric’ data type are perfect for this slot. The measure slot defines the numeric value of each box, which is a combination of the X and Y-axis categories. Different aggregations can be set to perform various calculations, such as the average.
12. Word cloud chart
A word cloud is a visual representation of text data where the frequency of each word determines its size in the cloud. This tool provides quick and straightforward visual insights into the most commonly used terms, making it easier to identify trends and patterns. By highlighting prominent words, the word cloud generator can help uncover significant themes and prompt further in-depth analysis.
What's next?
- Dashboard Builder: datasets explained: Check detailed explanations on the datasets available for your to connect to your
- Getting started with the basic widgets on your dashboard: Widget items: general.
- Check out these widgets to turn your dashboard data into meaningful insights:
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