I am currently a member of 40 LinkedIn groups mostly targeted at Master Data Management, Data Quality and Data Matching.
As I have noticed that some groups covers the same topic I wondered if they have the same members.
So I did a quick analysis.
With Master Data Management the largest groups seems to be:
- Master Data Management Interest Group with 2.818 members.
- MDM – Master Data Management with 2.333 members.
Using the LinkedIn Profile Organizer I found that 907 are members at both groups. This is not as many as I would have guessed.
With Data Quality the largest groups seems to be:
- Enterprise Data Quality with 784 members.
- The Data Quality Association (former European Data Quality Network) with 753 members.
Using the LinkedIn Profile Organizer I found that 189 are members at both groups. This is not as many as I would have guessed despite the renaming of the last group.
As for Data Matching I have founded the Data Matching group. The group has 235 members where:
- 77 are members in the two large Master Data Management groups also.
- 80 are members in the two large Data Quality groups also.
Also this is not as many as I would have guessed.
You may find many other similar groups on my LinkedIn profile – among them:
- Data Quality Pro.com with 252 members (main site has +2.000 members)
- Obsessive-Compulsive Data Quality (OCDQ) with 154 members (blog has heaps of visitors)
I’m convinced that is impossible to follow all the groups related to a topic. Because LinkedIn is based on collaborative mode, I believe that the Darwin law will make its work and all the too small groups will disappear. On my side I’ve decided to become member for the 3 biggest groups per topic.
Either the name of the smallest groups are not enough explicit and they have to be renamed either there exists redundancy and they will dead.
I think someone from the Data Quality area should contact LinkedIn managers to try to show them the possibility of grouping these groups into areas. It doesn´t make sense to exist two (or even more !) MDM groups where the obvious interest is the same. All groups should be grouped together according to general areas. I imagine it should apply to Wikipedia as well… Someone could get a LOT of money grouping these related groups…
Marcelo Valentim from Brazil
Graduate student at Information Quality at the University of Arkansas at Little Rock
Thanks Jean and Marcelo for the comments.
It really is a question about balancing the collaborative nature of social network services as LinkedIn and then how we as data quality and master data management professionals will like to solve uniqueness issues 🙂
Maybe group owners on LinkedIn should be able to merge with another group based on the acceptance of the group owner of that group and maybe group members should be able to suggest such merging?