Master Data Management with a DaaS Extension for Data Consumption at High Scale

Master data management (MDM) can secure a single source of truth of your data, enabling access to consistent and trusted key information across departments. In this way, MDM empowers retailers, distributors, manufacturers and financial institutions to enhance collaboration, operational efficiency, customer experiences, data analytics and many more operations that require trusted data. 

Governed master data can be delivered from the MDM to downstream systems, processes or parties who want to use that authoritative set of data. 

Scalability challenges 

In a traditional setup, it is common practice to build and maintain separate data stores with APIs between the MDM and the target systems to handle use cases that consume master data at very large scale, e.g., websites or point-of-sale systems. This provides a separation of concerns between complex master data processes and high-volume data consumption so that one activity doesn’t disturb the other. 

However, this entails a number of operability problems: 

• Building and maintaining a separate data store with associated API can be a cumbersome process 

• Data stores may easily become inconsistent 

• Allowing changes to master data to get through to consuming systems can take a lot of time since those changes may also necessitate development on the data stores

Service configuration

DaaS enables multiple services to be configured for the same master data, each with their own API, API keys and associated master data subset. Each API can be configured for maximum ease of consumption: 

• Easy to consume the data without having to understand the underlying data model

• No need to have the same data model in your application as in your MDM

• Fast and easy to adapt APIs to changes in your master data model

• You can change names of the objects and limit the scope of data to avoid exposing your entire data source to the application 

By making data available through an API service layer and serving data at scale on-demand for internal as well as external systems, the DaaS extension is a perfect example of the data-at-the-edge philosophy.