Master Data Integration

In a recent SAP Community blog series, Rui Noguiera outlined Master Data Integration as SAP’s corporate strategy for the Integrated Intelligent Enterprise when it comes to syndicating master data for a harmonized view across all applications. To achieve this, companies expect a coherent enterprise data model with common semantics that can be used to exchange data between business applications of the intelligent suite and its ecosystem. To fulfill this requirement SAP has introduced the SAP One Domain Model (ODM). A broad domain coverage of this model provides the underlying lingua franca for end-to-end process integration.

Fig: SAP One Domain Model is a model that enables the implementation of consistent APIs and reduces dependency on middleware to translate data structures and values. 

SAP has outlined this end-to-end process integration along four business processes (lead-to-cash, source-to-pay, recruit-to-retire, design-to-operate) and participating business applications. These four end-to-end processes cover a large percentage of the processes in a company. From the underpinning suite qualities, the “Aligned Data Models” quality plays a pivotal role in a master data integration context: As pointed out before, ODM represents the common language for master data and the MDI services represent the technological foundation to handle and distribute the data.

For more information about master data integration related to Recruit-to-Retire, see the SAP Community blog by Netin Datar.

Master Data Management

Companies can evolve their strategy for master data integration to active master data management. It is important to be clear on the difference between these disciplines and what organizations are trying to achieve with either of them.

While master data integration refers to the synchronization of master data across all applications in its current state, master data management is about improving the overall quality and trust level for master data. When it comes to master data management, companies typically prioritize their investments into quality for selected domains according to their business needs.

Fig.: Evolution of master data integration and master data management

From an MDG perspective, there has been an evolution starting from a point where mainly point-to-point connections were established across lines of business without any central strategy for managing master data. Then, with the onset of SAP Master Data Governance, a central master data hub has been put in place for enterprise-wide master data management including the syndication of governed master data across the landscape. Now, with SAP Master Data Integration services being in place to establish a unified master-data syndication approach SAP Master Data Governance will benefit by simply integrating to this master data sharing approach while continuing with its primary process goal which is getting and keeping master data clean based on its consolidation, central governance and master data quality management capabilities.

Fig.: Complementary disciplines: master data integration and master data management

As pointed out before, when it comes to master data integration, many organizations are striving for a very broad coverage of master data domains, because this is needed for end-to-end process integration. Accordingly, SAP is providing pre-built integration across many domains based on SAP Master Data Integration. By contrast, enterprise-wide master data management is rather focused on a limited number of master data domains, because the associated activities (for example, defining the process and data quality, defining and adjusting the organizational set-up, implementing the governance process across the enterprise) require significant investments. To put it in simple terms, the bigger the business impact, the greater the likelihood that an organization puts a specific master data domain under master data management.

In a nutshell, the out-of-the-box master data integration is complemented by SAP Master Data Governance to ensure quality and trust in master data. The combination of the two disciplines allows for new, very agile approaches for handling master data across an enterprise.

Impact of the evolving strategy for master data integration on current SAP S/4HANA and SAP MDG on S/4HANA implementations

In line with SAP’s architecture and technology guidelines, all applications and services that exchange or consume master data are planned to support SAP Master Data Integration over time. But as pointed out before and already explained in Rui Noguiera’s blog, this does by no means mean that this is a disruptive approach: It’s not about migrating existing integrations to SAP Master Data Integration in the short term, but rather about onboarding new applications in heterogeneous and hybrid landscapes.

Accordingly, integration capabilities such as the SAP Data Replication Framework (DRF) which is used by SAP S/4HANA and SAP MDG on S/4HANA are not planned to be abandoned and the features for syndicating master data across the landscape based on DRF will remain as a key capability. It is just that the upcoming option of handing over replication tasks to SAP Master Data Integration can open new levels of agility for operative S/4HANA systems and for SAP MDG on S/4HANA hub implementations that are used for global master data management. For example, by separating master data integration from master data management, the MDG hub can be shielded from high access loads from cloud applications. In addition, scale-in/scale-out capabilities with master data integration are perfectly tailored for flexible master data sharing in hybrid landscapes.

For information about this approach of integrating master data going forward, see the SAP Integration Strategy paper, read the SAP Help Portal documentation about SAP Master Data Integration and check the SAP Roadmap Explorer for the evolution of the Aligned Domain Model Suite Quality.

Best,

Markus

— minor update, link fixed Jan. 2021 —