In contrast to the components presented in the previous section that are made for visualizing aggregations over various dimensions, the aim of a Value KPI is to illustrate a single aggregation without any dimensions. In the following, the different options available when configuring a Value KPI will be explained.
An Aggregation can be added by simply clicking on the + symbol next to the column name. After adding an aggregation, you will see it in the list of aggregations on the right side of the aggregation selection field. Each list entry contains the column name the aggregation is based on, the first few letters of the field formula as well as two symbols for configuring and deleting the aggregation. If you click on the name or formula of the aggregation, an input field will appear allowing you to edit the respective field. The name and formula of an aggregation can also be changed in the aggregation settings which will be explained later in this section.
Apart from the field “Count”, whenever you choose an aggregation, you will have to select one of the four aggregation functions that is to be performed on the column selected. These four functions are “Sum”, “Average”, “Minimum” or “Maximum”. “Sum” will lead to the column entries being accumulated. “Average” will give back the average value of the column entries and “Minimum” and “Maximum” will lead to the minimum or maximum value of all column entries being chosen respectively. To learn more about Aggregations, please refer to Charts and Tables.
When choosing “Count”, no aggregation function needs to be selected. That is because “Count” simply counts the number of column entries for each occurrence.
You can also define your own aggregations based on PQL Syntax by adding an arbitrary column, e.g. “Count” and then entering any PQL based formula in the Formula field. How to edit the Formula field will be explained later in this Section.
Once you have added an aggregation, it will appear in a list on the right side of the aggregation selection field. After clicking on the small screwdriver icon, you will be forwarded to the edit menu. The following sections will explain the settings that can be made within that menu. The configuration menu is the same as the one for editing the dimensions and aggregations of Charts and Tables. Therefore, some of the options are not relevant for configuring KPI aggregations. This chapter will only focus on the options relevant for configuring a KPI aggregation. For a full description of all available options, please refer to "Charts and Tables (Analysis View)".
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Adding, editing and deleting of bands is only available if chose “Gauge” as your KPI type. These options allow you to define different sections within your tachometer and apply different colors to them. This can help to make your analysis more intuitively understandable. If you define green, orange and red areas for example, you will immediately be able to see, whether the value of your KPI is normal or critical. Figure 3.15 shows an example of a gauge chart with three differently colored bands.
Figure 3.15: Gauge Chart with three Bands
To add a Band, simply click on the small "Add Band" button appearing on top of the (initially empty) band list. After adding a band, an entry will appear in the list below and you will be able to edit the configuration options.
To delete on of the Bands, mark the respective entry in your Band list and click on the small "Delete Band" button on top of it.
If you hover over one of the heads of the columns within the Band list, a small arrow pointing down will appear next to it. Clicking on it will give you the option to sort your entries in the Band list in ascending or descending order. Also, you can choose which columns you want to display and which ones you want to hide from the list.
In the lower right corner of the Chart Configuration menu you will find the Filters button.
The Filters button is available in most components and gives you the possibility to define a filter that will be applied only to this component. If you apply a filter, only the data conforming to the filter criteria will be chosen as basis for the component. For the definition, any statement made in PQL Syntax can be used.