While deploying the MDM solution every enterprise chooses its own business rule by which they cleanse the consolidated data coming from different applications.
Since these rule varies across all the different organization so even though final data is cleansed but there is a question mark on credibility of the data.
At least without any international standard defined data quality rule I will not take those data as reliable and before presenting the facts based on the data I will always double check.
Un reliable data can have many negative consequences (The clinical data, space exploration results, in correct financial projection)
These data which is your master data but not credible can bring your company down in moments leave aside the regular maintenance work which you are doing to correct it.
Management team which makes decision based on this data looses faith quickly if data is not authentic and un reliable
The solutions
I have seen many people advocating that data credibility is not IT issue its rather business process issue and can be reduced if not fully by proper communication between data user and data creator.
My argument will be, see by this method we can reduce the error but not eradicate it fully, in the world of MDM and BIG DATA let IT people should jump to solve this issue before making it process oriented.
Logic to my argument
- Data Quality rules are not unique so make the rules as generalized and standard one.
- Organization should be certified if for data quality they are using those rules
- The volume or quantity of data is so huge that credibility cannot be tackled by business process
- Business processes can only tackle the data at the time of creation but they cant track in between when they changes drastically.
Incredible data lead you to losses your revenue, your customer faiths, so start defining your process,controls the incredible data usages and makes your business decesions based on true facts and not only on your master data
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