The data below is small that you would wonder why I bother blending and not join, or even creating a group. Let's say this is a demonstration of a technique that proved useful with much more big and complicated datasets, and where the non blending dimension of the primary source didn't have an obvious hierarchical relationship with the dimension in the secondary source that yielded the asterisk.
So we have two sources, the primary one lists European election constituency regions per UK nation. The secondary one lists all the MEPs with their region and party
So, how do we blend those two, and do a bar chart of the MEPs of each region with the appropriate party colour coding?
As you can see, once we put nation as a dimension from the primary source, the secondary source field 'party' cannot be used as a dimension, and we get the dreaded asterisk. Fear not, not all is lost.
There is a work around, but it only works for cases like this where there is a handful of Parties. We create a separate calculated field for each party's MEP, and use measure names on colour, and throw all these party MEP calculated fields on measure values (see screenshot above, calculations below)
if [Party]='CON' or [Party]='UUP' then [MEP] end
if [Party]='LAB' then [MEP] end
if [Party]='UKIP' then [MEP] end
if [Party]='SNP' then [MEP] end
if [Party]!='SNP' and [Party]!='CON' and[Party]!='LAB' and [Party]!='UUP' and [Party]!='UKIP' then [MEP] end
I've given a different scenario of
avoiding the asterisk with calculated fields in a blend in a previous post here
