When we kickoff our integration projects we run through a checklist with the client.
If they have been running the systems for a period of time, we always review the quality of the data, we call it a Data Quality Assessment (someone in marketing came up with that, not me, ok).
Usually, the client asks:
Why do I need a Data Quality Assessment?
- Have you been using the systems involved for some time?
- Have you tried to keep them in sync manually? For example: Create Company ABC in both Salesforce and RightNow manually.
If you have, then our advice is to assess the quality of the data before investing in integrating the systems. If the data isn’t cleaned now, we’ll increase the problem once the systems are integrated and bad data is being synchronized.
What’s involved in a Data Quality Assessment?
This involves profiling your data to review if the data is ‘clean’, ie do you have excessive duplication and can we merge records to clean this quickly.
What if I don’t clean the data?
Consider the following example:
1) The process for Account/Contact creation in Salesforce is a manual process done using the information in Right Now:
2) Given the manual data entry it’s possible for the following to exist:
3) When we integrate we will end up with RightNow Case and Opportunity data linked to the wrong Salesforce Accounts.
This is what would occur after running the integration process on the above data:
Looks messy right? Definitely, something for you to think about before connecting the systems. IMO some type spent up-front will save a lot of pain and $ in the long-term.
It would be like eating healthy food for a week.