There are a large number of different solutions regarding Data Management, this abundance might make choosing which solution to start a project difficult and overly complicated. My good friend Dev wrote a great article on the technical differences between MDM and MDG, so in the following article, I would like to expand on the idea and present a brief overview of possible scenarios for each solution.
SAP Master Data Manager
Master Data is the definition of a data element, a common data object throughout all organisations and systems. SAP MDM is usually used together; Web Dynpro (and other UI frameworks), BPM and Enterprise Portal to provide a simple yet powerful data management process to users. This solution is recommended for those objects that are unstructured and the management process is not yet defined (i.e. spreadsheet replacement).
SAP Master Data Governance
MDG is SAP’s attempt to better integrate Master Data processes with traditional ECC systems, not only does it define a common data object and provide a repository for it, it also provides a way to better define the whole data maintenance process by integrating more efficiently with SAP Workflow and Web Dynpro ABAP. This solution is preferred in scenarios where the governance process is as important as the definition of the data element. Nowadays, most companies are at a data maturity level where MDG is a very powerful tool.
SAP Business Objects Data Services
Sorting out the mess! Data Services is especially useful when you have a mix of different systems that require data governance, Data Services centralises data management rules and since these rules can be shared via web services, it allows the reuse of rules throughout your environment. This is especially useful in very fragmented organisations trying to establish a central Data management team.
SAP Business Objects Information Steward
A RIRO (Rubbish in, Rubbish out) preventer. Information Steward can provide a data quality cockpit that allows you to see what your major data quality problems are and take preventive measures. This is especially useful for de-duplication process, data quality maintenance and in a unification process, so that any existing data object can be identified and merged effectively.
Enterprise Information Management
Wrapping everything up. The culmination of all different solutions and governance processes into an effective and efficient information management process. The key to good EIM practice is, not to rush into it; data management must grow organically in order to be effective. Rushing into a complex and lengthy management process is a sure-fire way to bloat the overall solution and waste money. Where, how, when, by whom and until are the main questions a good Enterprise Information Management strategy must answer.
When making a choice on how you will handle your master data, make sure the solution you pick is right for the data object you need it for. If you need any help or just want to throw some ideas around, feel free to contact us.
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