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Implementation - Centralized MDM

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Low-code data integration

Finally, a Master Data Management platform that anyone can use. OpenAI integration lets any business user master data without technical expertise - just type a plain language prompt, hit enter and it's done. 





Establishing a centralized repository for master data

Centralized MDM involves establishing a centralized repository for master data while allowing individual systems to maintain local copies for operational purposes.

This approach ensures a single version of master data while allowing decentralized data management. Centralized MDM supports data consolidation, data quality management, and data governance in a controlled and governed manner.

Local systems can synchronize data with the centralized repository periodically or in real-time to ensure consistency.

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Benefits of centralized MDM:

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Consistency & control

Provides a centralized master data repository for consistency and control.

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Performance

Allows operational systems to maintain local copies for performance and autonomy.

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Data governance

Enables data governance and stewardship at a central level.

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Data integration

Streamlines data integration and data sharing across systems.

Challenges of centralized MDM

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Data modelling

Similar to Consolidated MDM, in the past the Centralized style has dictated that data teams model their data upfront – before they have even started to use the MDM system itself. This process can take six months or more, by which time the likelihood is that the model is out of date and of little use.

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Operational system autonomy

Balancing the need for centralized control and governance with the autonomy of operational systems can be complex. Ensuring that local systems can maintain and update their data while adhering to data standards and governance policies requires careful coordination and communication.

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Data synchronization

Centralized MDM requires synchronization between the central repository and the local copies in operational systems. Ensuring timely and accurate data updates across systems can be challenging, especially in distributed environments.

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Change management

Implementing centralized MDM may require significant changes to existing systems and processes. Managing change, addressing resistance, and ensuring smooth transition and adoption by stakeholders can be challenging.

Use case example...

An e-commerce company with multiple online stores wants to maintain centralized control over product data while allowing each store to manage its inventory. Centralized MDM enables them to have a single, authoritative product catalog, while individual stores can update their local inventory as needed.

How CluedIn solves centralized MDM challenges

CluedIn addresses common centralized MDM challenges in the following ways:

Manuel data entry forms

CluedIn can create Manual Data Entry forms for the creation of new data directly into the platform.

Power Platform integration

Data can also be created by Excel Plugin or by Power Apps. We use our Power Platform integration via Power Apps and Power Automate to support this.

Data streaming to source systems

Newly created data can be streamed to source systems using the most appropriate integration pattern for the receiving system. 

View our MDM Implementation styles white paper for the complete overview

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