Business analysts take mountains of data and drill down to granular levels in order to extract value and meaning. CoolaData’s Virtual Columns aid in this process by enabling the inclusion of additional metrics, as if they were columns in a table. This new information can be used to target selected users, ultimately leading to better engagement.
A great example is the analysis of different age groups. Age data is typically sent to CoolaData as an actual number, but the business need is usually to segment various ages into groups and then use those groups to engage a range of users effectively.
Virtual columns are created and calculated when relevant event data is sent to CoolaData. If ‘age’ is the entity sent to CoolaData, then the range definition of segmenting people between age groups (such as ‘21-30’, ‘31-40’, etc.) can be set up. CoolaData then places individual ages into the right range in the form of a virtual column.
CoolaData customers implement their own virtual column logic with basic SQL syntax. We aggregate the data into new columns based on customer preferences.
An eCommerce Purchase Example: Currencies
Data sent to CoolaData often includes events associated with an eCommerce purchase. This data could be the purchase amount, items purchased and so on. When a price is stored by default in US dollars and an analyst wants to convert it to euros, virtual columns can be set up (along with the dynamic conversion rate) to handle the conversion.
CoolaData widgets that support client-side calculations (our CQL, Fusion and Power KPI widgets) offer a listing of all available columns for the widget (as seen below on the left), as well as a form for entering a new calculated column (below on the right).
See our Documentation for more on the benefits of using CoolaData’s virtual columns.