Different architecture approaches for deploying MDM exist since every firm is different, with its own array of requirements, IT landscape, and business processes.

Analytical MDM, which focuses on feeding consistent master data to data warehouses and other analytics systems, and operational MDM, which focuses on master data in core business systems, are two types of master data management that can be implemented separately or in tandem. Both offer a systematic approach to master data management, which is often made possible by the deployment of a centralised MDM hub where master data is kept and maintained.

Each has its own set of benefits and disadvantages, and picking the best option isn't always easy. When selecting how to proceed with Master Data Management in a business, the available money, the IT landscape, the existing organisational structure, the individuals involved and their skill set must all be carefully evaluated. When it comes to master data management architectures, these are three basic types of master data management architecture that can be recognised.

Read: What is Master Data Management

Registry Architecture

For downstream systems that must read but not alter master data, this design gives a read-only approach. This implementation architecture is beneficial for reducing duplicates and ensuring that master data is accessible in a consistent manner (in many cases distributed).

The master data attributes that are necessary to guarantee uniqueness and cross-reference information to the application system that maintains the whole master data record are frequently only a narrow slice of the data in the MDM System. Except for the attributes persisted in the MDM System, all characteristics of the master data attributes remain with low quality without harmonisation in the application systems in this scenario. As a result, the master data in the (MDM) System is inconsistent and incomplete in terms of all properties. This master data management architecture has the advantage of being relatively rapid to deploy and less expensive than other master data management(MDM) architectures. Also less intrusive are application systems that provide read-only views of all master data records in the IT architecture.

Hybrid Architecture

This master data management (MDM) architecture effectively materialises all master data attributes in the MDM system. Master data can be created using MDM and application systems. All traits are present in terms of completeness. However, only convergent consistency is provided in terms of consistency. The reason for this is that modifications to master data in application systems disseminated to the MDM System take time to synchronise. This indicates that consistency is on the right track. The smaller the propagation window, the closer this implementation design comes to being flawless.

The cost of implementing this architecture is higher because all master data model attributes must be harmonised and cleansed before being loaded into the MDM System, making the master data integration phase more expensive.It is also not free to synchronise MDM systems with application systems that modify personal data. This technique, on the other hand, has a number of advantages that the Registry Architecture implementation lacks:

  • The quality of the master data has greatly increased.
  • Because federation is no longer required, access is usually faster.
  • Cooperative master data creation workflows are much simpler to start up.
  • Because all master data attributes are now centralised, reporting on master data is easier.

Read: Benefits of Master Data Management

Repository Architecture

This master data management (MDM) architecture ensures that master data is always consistent, accurate, and complete.The MDM System now manages both read and write actions on Master Data, as opposed to the Hybrid Architecture. To do this, any apps that require master data changes must use the MDM services provided by the MDM System.

As a result, the delay caused by propagation of new master data is avoided, resulting in 100 percent consistency on master data.

With this master data management (MDM) architecture, deploying an MDM solution may necessitate better infiltration into application systems, monitoring business activities so that they communicate with the MDM System for master data changes, or deploying global transaction procedures like a two-phase commitment architecture.


A master data management (MDM) architecture often comprises change management, workflow, and collaboration capabilities in addition to a master data storage repository and software to automate interactions with source systems. Another technology option for augmenting MDM hubs is to use data virtualization software; it produces unified views of data from many systems virtually, without requiring any physical data migration.


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