The data input for all chart visualizations is a table, with one or more fields, and one or more rows. So, the default view when creating a widget in SAP Signavio Process Intelligence is a table.
Based on your analysis and visualization goals, you need to configure this table of data using aggregated attribute values about your data (measures) and attributes by which you want to segment or group your data (dimensions).
Assume, for example, you want to determine how long it takes, on average, from order placement to goods delivery for different customer types, such as 'standard' and 'premium'. Then, the average of the aggregated cycle time is the measure and the customer type is the dimension.
By combining different measures with different dimensions, you can create views of your data that can be used to visualize the data according to your needs.
Measures and Dimensions
In general, when looking at data, dimensions and measures are assigned according to the type of attribute, and usually the following applies:
- Dimensions are qualitative, in other words, not numeric
- Measures are quantitative, so you can perform aggregation calculations on them
In SAP Signavio Process Intelligence
Here, dimensions are the qualitative data that make up your data set, called event log attributes. Examples for event log attributes are 'case_id', 'customer_id', 'customer_type', 'city', and 'order_category'. You can use dimensions to segment your data into categories, often referred to as grouping your data.
Measures are aggregated values derived from the quantitative attributes of your data, for example:
- The count of cases, calculated by COUNT(case_id)
- The average order amount, calculated by AVG(order_amount)
To determine a measure based on an attribute, you first select that attribute, and then choose the calculation to achieve the desired aggregated value.
Measures return one value if there are no grouping dimensions. If dimensions exist, then one value is returned for each distinct group within the dimension.
Metrics, which are a type of measure, are pre-defined for easy reuse.