…covering everything which includes the word "data" or "information"
Although choosing the right data hub style depends strongly on the MDM requirements apart from other several other factors, it seems that the logical approach to implement an MDM solution would be registry style -> hybrid style -> repository style.
However, this may not be the best approach because the registry style does not tackle data quality issues except for de-deplucation and therefore is less likely to impress the business. The repository style would take too long to implement to demonstrate some value of MDM. For this reason, the hybrid data hub style is mostly a good way to implement an MDM solution.
You can start with only a few attributes. As the data management and data governance capabilities within the organisation improve, you can add more attributes to the data hub until all attributes are covered. The next step then is to migrate the registry style attributes to repository style attributes. This will help to gradually build a complete repository style data hub. Systems which had not been included as part of the MDM solution will some time in the future be replaced. At the point when a new system for replacement is introduced, you can configure it to use the repository style data hub.
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The purpose of this blog is for the author to share his knowledge and experience in various Data Management domains with the aim of helping readers to learn/expand on their existing knowledge in the area. This blog shares knowledge on Master Data Management, Data Quality, Data Governance, Data Integration, Data Analysis, Data Profiling, Data Warehouses, Data Marts, Data Modeling, Data Architecture, Metadata Management etc.
I am Manjeet Singh Sawhney and work as a Data Architect for Direct Line Group in Bromley (UK). Prior to this, I have worked for Accenture, Tibco Software, Initiate Systems (now IBM) and Tata Consultancy Services. My areas of expertise are Master Data Management (Customer, Product, Reference), Metadata Management, Data Governance, Data Quality, Data Integration, Data Migration, Data Warehouses, Data Marts, Data Modeling, Data Architecture, Data Profiling and Data Analysis. I am using this blog to share my knowledge and experience in these areas and hope that you will find it useful.
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