I am doing an analysis to find out the related customers and their distance if a customer ID is provided. For e.g.,
A - is the primary customer ID which has SSN, Mobile Number, Email ID and CR Number. So A is customer 0.
W - is having the same mobile number, hence W is at distance 1.
K - is having same email ID and SSN same as A, hence K is also at distance 1 but a different mobile number.
P - having same mobile number of K but there is nothing in common with A. As A is related to K with email ID and SSN, and P is having same mobile as K, P is a distance of 2 from A.
M - having same email ID of P, then M is at a distance of 3 from A.
I did this whole network in a tabular format from 6 million customers that we have. Now, I want to display a nice network map something like below.
Hi @rfeigel, My organization does not allow to upload any data. I can only copy and paste. Hence, I took this approach. Let me see, if I can put in a CSV file and share it again. distance_to_share.csv (2.0 KB)
Could you explain what you’re trying to network, i.e. customer names? Also some of the data elements are unclear as to how they would be used:
Customer Number Previous
Match
Email ID - many missing
CR_NO
Mobile_No - many duplicates which seems odd.
I’ve tried to pare down the dataset, but I’m unsure what to use.
You haven’t replied to my last post. I developed a workflow which produces this network with the object configuration below. Its the best I could do with the data you supplied. Maybe others can do better.