Charts are divided into the following categories:
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Comparison charts show comparisons between two or more categorical values.
Bar/column charts are used to compare measures based on dimensions. The value of a measure is represented by the length of the bar, while dimensions provide the axis of the chart.
When bars are horizontal the visualization is considered a bar chart, vertical bars are considered a column chart.
When a color dimension is selected, bars or columns will automatically cluster to show the breakdown of the measure over the included dimension.
An alternative to a clustered bar/column chart is to use a stacked bar/column chart. When bars/columns are stacked, they show the total measure divided into selected dimensions.
Combination Column and Line
This chart type displays one measure as a column and a secondary measure as a line. The two measures are usually displayed over a time dimension. This chart is useful for showing the relationship between two measures over a period of time.
Combination Stacked Column and Line
A combination stacked column and line chart should be used in a scenario when the goal is to show trends as well as a breakdown of a particular measure in relation to a dimension.
Use a waterfall chart when you want to show the positive and negative changes that a measure goes through according to a dimension (usually time).
Charts that fall under this category are typically used to show trends over time.
With line charts you get an overall picture of your selected data by communicating upward and downward trends and overall volatility.
Line charts can also be used to track more than one data series on the same chart. This helps to reveal any correlation in trends.
Like line charts, area charts are best used to depict a time-based relationship. However, area charts also represent volume and are most useful for communicating an overall trend over time, as opposed to individual data point values.
Stacked area charts can be used for multiple data series with part-to-whole relationships or to show a cumulative series of values.
Another option to show trends over time is a time series chart. By choosing a time series chart you’ll easily be able to filter by different time periods.
A feature of the time series chart is the ability forecast future values based on historical data within the chart.
The correlation chart type is used to show whether the value of one measure impacts the value of another. Color coding dimensions can deepen the meaning of correlation charts, but is not always required for analysis.
Use a scatterplot to find out whether or not there is a correlation between two specific measures.
To see the correlation between three measures use a bubble chart. They display a measure on each axis and a third measure is reflected in the size of the bubble.
This style of bubble chart is another way to show the value of a measure based on two dimensions. The best way to explore a cluster bubble chart in SAP Analytics Cloud is by hovering over each bubble to display the tooltips that contain more detailed information.
Charts in the distribution category focus on displaying the distribution of values within a dataset
Box plots show the distribution of data based on a five number summary: minimum, first quartile, median, third quartile, and maximum. When datasets have single points with extremely high maximums or surprisingly low minimums they’re displayed as outliers.
The dimension tool tips on a box plot will show the breakdown of the 5 number summary, as well as the number of outliers and values within the data.
The tiles on a heat map change color based on the value of the measure. Heat maps are a convenient way to represent a large volume of data points in a chart that’s easy to read.
Histograms are easy-to-read charts that allow you to compare quantitative data in a visually compelling way.
The tree map chart type functions similarly to heat maps. The difference is that the dimension tiles change in size depending on the value of the measure. Tree maps are limited to a single measure and dimension per chart.
Radar charts are useful for seeing the distribution of values across dimensions and what the outliers are. They can be used to see which dimensions are scoring high or low for a particular dimension, making them ideal for displaying performance.
Charts in the indicator category are a quick way to show current values or a level of progress.
A bullet chart type can be used to indicate progress towards a goal. To use a bullet chart in SAP Analytics Cloud you must first establish thresholds for the measure you are working with.
Use a numeric point chart type to show totals at a glance. Numeric points can also be enhanced with thresholds. When thresholds are enabled the color of the number changes to show where it falls within the threshold.
The charts in this category are used to show both part-to-whole relationships and distribution of measures.
Pie charts and donut chart type are used to show the percentage of a type of dimension within a measure. The entire pie or donut should always add up to 100%.
Thresholds can also be added to pie/donut charts to show a quick view of a status of a dimension in relation to a goal.
The Marimekko chart is bar style chart type that communicates through width, rather than height alone. This allows for each bar to communicate two measures using the size of the bar as well as two dimensions by stacking values of dimensions in a single bar and the axis labels.
The International Business Communication Standards (IBCS) is not a chart type per se, but rather a conceptual design guideline for conveying business information in the most concise manner to enhance understanding. In the examples below, we’re seeing two IBCS charts — one comparing absolute values and the percentage values. You can see that the variance is shown in green for positive values and red for the negative values.
The black and white variance chart shows data from the previous year (PY) for January to September as well as the actual (AC) data for the same time frame. We also see the data from the previous year (PY) compared to the Forecast (FC) for October to December.
To learn more about IBCS charts, please visit our IBCS playlist.