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As information about their customers change, the difficulty of keeping all the systems up to date becomes exponentially more difficult as the number of systems increases.
Considering the diagram above:
- Where is the truth? A
A customer's email address would be stored on several systems and there may be conflicting values. If this is the case,
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which system holds the truth?
- Which system gets notified of a change and what data elements do other systems need?
If all systems need to be updated, then each system needs to know how to transform the data to be consumable by the each of the other systems, which requires programming many transformations.
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In an extreme case, the example above could take five transformations for each of the six systems
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, totaling 30 transformation modules or adaptors.
- Are changes handled in real time or in batch?
The easiest and most common change handling is via batch updates. However,
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the latency between batch updates usually causes issues with business processes.
- How is DI handled? The
The onus of transferring data between systems becomes a daunting task. While some applications have built-in adaptors to handle transformations they generally handle only a subset of what is required. Where the built-in adaptors fall short or don't exist, the organization has to spend resources developing adaptors as "one-off" applications to meet the ongoing transformation need.
- How does the organization manage access to the data? Perhaps
Perhaps the Warehouse should get access to only a subset of the customer data or shouldn't get any level of access to the Credit Card Processing system.
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The term Governance is used to describe managing access to the data.
The problem doesn't end with just the customer data as other . Other data such as product, inventory, and employee data may need to be kept up to date on several systems as well:
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Master data management (MDM) solves this problem the problem of keeping interrelated systems up to date by creating a separate system where data domains (or domains) are defined for all systems inside the organization. The domains provide neutral data formats or schemas for all systems. A YOUnite MDM a domain can either:
- Centrally save the latest change of a record (centralized MDM) or,
- It can make note of when a change occurs in one of the organization's systems without actually storing the data in YOUnite; this is called federated MDM.
The latest version of a customer record is called the customer's Master Data Record. , or MDR. So in
In the example of our delivery service:
- In a centralized domain, the MDR is stored by YOUnite and can be retrieved, in whole or in part, by applications that have appropriate access.
- In a federated MDM implementation, the MDR is NOT stored inside of YOUnite but is created in real-time by referencing the elements (or properties) as they reside inside the various systems. An identical property is often stored in multiple systems.
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- Data Integration (DI) The process of transforming and transferring data from one system to another
- Adaptor Applications, modules or some software or hardware component that transforms data from one format to the other so that the data can be consumed by another system.
- Governance Managing access to the data.
- Data Domain (Domain) A set of fields or properties that define a set of data.
- Master Data Management (MDM)
- Master Data Record (MDR)
- Centralized MDM
- Federated MDM
- Scope
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