Hi Ed and Ted
We went through something similar to this a number of years ago when one of our life sciences customers was migrating away from just over 60 separate legacy MDM instances around the world to Reltio. The original assumption was that we would preserve match rules in each of the regions because a lot of time was spent designing the rules and each region had its own "unique" needs. After gathering all the distinct match rules (Over 130 if memory serves), it became quickly apparent to the stakeholders that
A) there are only so many permutations that actually make sense before you go into crazy land when it comes to matching and
B) a simpler model is way easier to maintain and can deliver good results quickly. So the net was an initial set of common rules that worked well across regions and then if a particular region felt they had some very unique needs, the data governance team would review and decide if they wanted to add some specific rules (with filter conditions).
Hope this helps. Guy
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Guy Vorster
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Original Message:
Sent: 09-27-2021 15:08
From: Ed Mosier
Subject: Data Modeling and Governance Scenario
Ted,
That was my original thought too, but wasn't sure if that's what the consensus would be. This is a hypothetical scenario but I feel that it illustrates some design considerations when there are large implementations with complex governance structures in place, each with different business rules.
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Ed Mosier
Slalom
MO
Original Message:
Sent: 09-24-2021 11:14
From: Ted Sager
Subject: Data Modeling and Governance Scenario
This is such a interesting use-case.
Wouldn't the desire to define state specific match rules/validation/cleansing and more importantly survivorship necessitate an entity per state model?
I can't imagine it would be pretty to try and maintain up to 50 survivorship variants * n attributes. Even if you could, the reality of 50 different governance teams trying to make releases would be... stressful.
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Ted Sager
Qlik
Original Message:
Sent: 09-15-2021 18:30
From: Ed Mosier
Subject: Data Modeling and Governance Scenario
Looking for some feedback regarding best practices around data modeling and governance.
Hypothetical situation
- Implementing account 360 as a starting point.
- Data will be coming in from different states
- Matching will be configured to only match when the states are the same.
- Each state has Data Governance team that sets
- Matching rules for their state
- Survivorship rules
- Cleansing / validation may need to be handled at the state level as well
- Roles will be created based on states so that privileges will be set at the state level (e.g. someone with access to CA should only see CA data)
Considering the above, is it generally best practice to:
- Use entities Organization and Contact with a state field or
- Create state specific Organization and Contact entities that extend Organization and Contact
For #1,
- I would be concerned with matching as the number of match rules could easily exceed 100+, much more than the recommended max of 10 per entity. Would this matter since they would all have an exact state match as a component?
- The maintenance and security configuration may be more difficult since everything would be done on two entities, but filtered by state. Would this be the case?
- Are there any other performance considerations?
For #2,
- This would multiply the number of entities by the number of states configured. Would this be a concern? I didn't see anything related max entities in a model.
Any feedback would be greatly appreciated.
Thank you,
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Ed
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