The merged data group type is one of the collection of data manipulation types: filter, group, merged, pivot and relative.

A merged data group brings together the contents of other data groups (other than data manipulation types) to form a new set of data. This new data can then be treated as a new single set of data.

For example, if you have different time based information about a client such as calls, activities, orders, deliveries and so on, you can create a single chronology from these even if the data is in different data sources.

To create a merged data group simply select which data groups to include from the list of available data groups. Note that since data groups are processed in order you can only merge data groups that are higher on the list than the merged one.

All fields from all specified data groups will be available so it’s worth considering the way in whcih you construct the data groups. If at all possible, use common field names across all specified data groups so that these are available in the merged data group automatically.

If you can’t do this, use data items in the merged data groups to create common fields by referencing fields in each specified data group. A “mergedFrom” field is automatically provided to help with this:

=CASE(=VALUE(mergedFrom,mergedDG),=VALUE(ActionDate,mergedDG),Orders,=VALUE(OrderDate,Orders),Invoices,=VALUE(InvoiceDate,invoices))

In this function the required field is taken from the ActionDate filed in the mergedDG data group unless the row was merged from either the Orders or Invoices data groups when the OrderDate and InvoiceDate fields are used respectively.

This technique can lead to quite complex functions, so always try to create common field names where possible.