After you have successfully created a Dashboard via the Dashboard Configuration, you can open the specific Dashboard by hovering over Dashboards in the top menu and clicking on a particular dashboard.
You can now modify how data is being displayed in the charts.
Line Chart
- Aggregate the visible data by choosing an aggregation level e.g. day, week or month level (1)
- Display the data by choosing a date range (2)
- Show/hide data by choosing a data type in the legend (3)
- Display the chart in fullscreen mode (4)
Bar Chart
- Get more detailed information about the displayed data by hovering over the bar chart or dive deep into the displayed elements by clicking on a bar (1)
- Show the chart in fullscreen mode (2)
Pie Chart
- Get more detailed information about the displayed data by hovering over the pie chart portion or deep dive into the displayed elements by clicking on the pie chart portion (1)
- Show/hide data by choosing a data type in the legend (2)
- Display the chart in fullscreen mode (3)
Table Chart
- Get a structured overview of your numerical data in the form of a table chart
- Configure a list field / dropdown field (1) as the segmentation category for the rows, in this example Type of Innovation & Development, and select one or multiple numeric or calculated fields (2) as the column segmentations of your table view, here the numeric fields Budget 2024-2026
- Have the system automatically calculate the row and column totals of your table view by sum aggregating the assigned values of the underlying elements (here Project elements) for both the rows and columns (3)
- Optionally make use of the heat map coloring option to color the highest value(s) per column based on the primary system color (75%-Quartile) and the lowest values per column based on the secondary system color (25%-Quartile).
- Display the chart in full screen mode or assess any chart-specific filters (4)
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In the table chart configuration, there is the possibility to select the underlying Aggregation Type for the table chart. Per default, SUM aggregation is selected, however, the following aggregation types are supported to visualize the numerical date in the table chart:
- Sum
- Average
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Median
- Middle value of a data set when the numbers are arranged in order. If there’s an odd number of values, the median is the middle one. If there’s an even number of values, the median is the average of the two middle values.
- Example: Data set: {3,1,4,2,6} → Arrange the numbers: {1,2,3,4} → middle two numbers are 2 and 3 → Median = 2.5
- Minimum
- Maximum
- Count
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Count unique values
- Counting the number of distinct (unique) values in a data set, ignoring duplicates
- Example: Data set: {3,1,4,3,4} → Unique values: {1,3,4} → Count of unique values = 3
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Sample variance
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Measures how spread out the data values are from the mean. It is calculated by:
- Finding the mean.
- Subtracting the mean from each data value and squaring the result.
- Summing those squared differences.
- Dividing the sum by n−1 (where n is the number of data points).
- Example: Data set {3,1,4,2,6} → steps to calculate the sample variance:
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Sample standard deviation
- Measure the spread or dispersion of a data set. It is the square root of the sample variance. While the variance gives the squared deviations from the mean, the standard deviation is in the same units as the original data, making it easier to interpret. It gives a sense of how much the values in the data set deviate from the mean on average.
- Example: Data set {3,1,4,2,6} → steps to calculate the sample standard deviation:
- Measure the spread or dispersion of a data set. It is the square root of the sample variance. While the variance gives the squared deviations from the mean, the standard deviation is in the same units as the original data, making it easier to interpret. It gives a sense of how much the values in the data set deviate from the mean on average.
Note: one use case could be the combination of the Average aggregation type with the Date Field Calculation option. This way, a table chart could be created that visualizes the average times that elements remain in a certain workflow phase by calculating the average time that elements of a certain row category remain between a start and end date field.