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SAP MDG Architecture

Organizations expanding globally and social media a major part of the business environment, digital marketing poses increased risks to master data management due to an increase in complexity and volume. It is imperative to have a solid structure in order to manage, organize, manage, govern, and optimize data. This is precisely where the SAP Master Data Governance (MDG) architecture comes into play. Let us understand how it offers a comprehensive solution for managing and optimizing data within this dynamic environment.

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The SAP Master Data Governance (MDG) architecture is a robust framework transforming organizations' handling of vital data. An effective data management solution is crucial with global expansion and rising digital complexities. SAP MDG is a cutting-edge system enabling seamless creation, sharing, and modification of data across the entire enterprise network. It ensures data integrity within SAP systems and across non-SAP systems.
At its core, SAP MDG architecture streamlines processes, boosting productivity, cost-efficiency, and time management. Its primary goal is to enhance the quality of business and product data. It covers aspects like data usage, business partners, and product information by aligning technical implementations with business needs and ensuring consistent data quality. Collaboratively defining catalogs and implementations, SAP MDG forms a robust foundation for data quality evaluation.

SAP MDG architecture facilitates quality evaluation and analysis, offering insights into data integrity. This empowers businesses to grasp their data's quality and conduct multi-dimensional analysis, ensuring accurate, error-free data. By maintaining data excellence, SAP MDG architecture enhances business operations and equips enterprises to navigate the modern data landscape confidently.

SAP MDG - Table of Contents

What is SAP Master Data Governance (MDG)?

SAP Master Data Governance or SAP MDG provides central ownership of master data in line with a company’s business rules and processes. MDG delivers domain-specific, out-of-the-box applications as well as a framework for custom-defined master data. SAP MDG architecture offers change request-based processing of master data with integrated workflow, staging, approval, activation, and distribution. MDG can be deployed as a separate hub system, or co-deployed with SAP ERP.

In both cases, MDG can use SAP and company-specific business logic to create master data ready to be used in a company’s business processes.

SAP MDG architecture consolidation provides an understanding of enterprise master data that is owned and maintained de-centrally. SAP MDG solutions, consolidation delivers capabilities to load master data from different sources, to standardize the master data, and to detect duplicates. For each of the resulting match groups, MDG calculates a best record out of the duplicates in that group, using survivorship rules on the master data attributes. These best records can then be used in dedicated analytical or business scenarios.

Within SAP Master Data Governance you can combine consolidation and central governance to support various master data management scenarios, like initial load of master data as a starting point for central governance, consolidation of master data after mergers and acquisitions, or combinations where you keep de-central ownership of master data in some parts of the company while centralizing master data ownership in other parts.

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Key Capabilities of the SAP Master Data Governance

Now that we are familiar with what is SAP Master Data Governance, let us move on to its key capabilities. 

1. Defines the Data Quality

With the help of SAP Master Data Governance, the requirements will be defined that are based on the company’s business process. The priorities of the business are set according to the values and quality evolutions. Also, the business experts collaborate to check the quality and other required checks.

2. Ensures the Data Quality

SAP Master Data Governance ensures the data quality at each entry point. It also offers rules-based checks in all SAP Master Data Governance business end points.

3. Monitoring the Business Quality

This step can be categorized into three parts- data operational motivation, tactical, and business strategies. Data operational motivation helps in the detection of all issues before processing them for the next level of operations. Tactical help businesses ensure the progress and the performance regarding the ongoing business activities. Lastly, business strategies enable users to achieve goals. Also, it defines the initiatives so the process of data monitoring and trend reporting becomes easy.

4. Improve the Quality

SAP Master Data Governance corrects the data. It also drives the correlation process. Some more functions of this include evolving data quality definitions and fixes the data entry processes. It also offers several tools to fix the data and check for the data entry processes.

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Advantages of SAP MDG Architecture

  • The SAP MDG ensures data centralization, compliance, transparency, master data creation, integrated staging, central auditing, and data approval.
  • SAP MDG helps in the delivery of consistent data, authorization, and replication of the master data key representatives.
  • Helps to eliminate the error-prone manual maintenance process for the master data across multiple systems.
  • Enables organizations to create centralized data to define the key records and mapping between the duplicates.
  • Defines the master data quality, consistent data usage across all data entry points monitors the data quality, and analysis.
  • Helps organizations to observe and investigate the master data management quality to enable data optimization.
  • Offers native integration and openness to integrate with 3rd-party services.
  • Reusing SAP data models, business logic, and data validation configurations. 
  • It acts as an open application to manage master data, and check for the flexibility of the non-SAP environments.

Key Benefits of Master Data Governance Software

1. Central Governance – Workflow routing and connected system notifications allow different organizational teams to govern their data more effectively. With SAP Master Data Governance, SAP users can own and control their master data attributes, improving the transparency and compliance of important data in the entire process.

2. Data Consolidation – Mass updating and processing large amounts of data is easier in SAP data governance. This is because it provides a single source of truth to connect all SAP and non-SAP data sources. SAP Master Data Governance consolidates master data within your system. It also simplifies duplicate mapping and builds the most accurate record for your data. 

3. Quality of Data and Analytics – Integration with SAP smart business and data services simplifies data measurement to improve the quality of data across your organization. SAP data governance solutions help users build business rules to manage and control data quality for further analysis of the performance of important master data.

4. Seamless integration – SAP Master Data Governance possesses the capability of integrating with other SAP modules and applications seamlessly. These modules include reuse of data models, business logic, and validation standards. The solution also leverages a standard model to integrate SAP and non-SAP systems without much effort.

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Applications of SAP MDG

Till now we have seen the architecture overview, benefits, and key abilities of the Master Data Governance. Now it is time for us to know what are all the various industries that make use of MDG architecture to boost up the data quality and management.

  • SAP Master Data Governance for financial business - For example; financial/ accounting data consolidations, profit, and cost centres.
  • SAP Master Data Governance for the supplier data - For example; corporate, companies, partner functions, and purchasing related data.
  • SAP MDG solutions for the customer data - For example; sales related data, and partner functions.
  • SAP MDG for the material data - For example; corporate industries, sales organizations, storage, plants, warehouse, and costing data.
  • SAP MDG solutions for enterprise assets management data - For example; equipment, billing, and functional locational data.
  • SAP MDG for fashion and retail management - For example; hierarchies, single and generic billings, listings, and characteristics variants.
  • SAP MDG can also be used in data models, user interfaces, and governance for the master-related data.

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Process Flow of SAP Master Data Governance

1. Data load

Data load is the first step in master data consolidation of the source records. The process flow diagram above shows the data import from the file. You can fill the data in a .csv file or .xlsx file in a predefined format that the consolidation system accepts

2. Enables Initial Check

This process flow allows users to view loaded data, and check for the data quality based on customization.

3. Standardize

Standardize the data quality Validation and enriching the data addressability. Possibility to connect through the 3rd-party vendors for the standardization and data enrichments. Usage of BRF (it is a tool that is used to define both technical and functional rule sets). 

4. Data Matching

SAP MDG solutions helps users to find duplicate data based on the customer specifications and review the data matches.

5. Data Validation

Helps in the validation of the best records against the backend customizations to check whether the records are activated or not. Data validation can also be done against control governance checks (for example, BADI (business adds in), and BRF).

6. Calculates the Best Record

Initially, it creates the best records based on approved match groups. The BRF can be used for customer-specific best record calculations. The final step includes the reviewing of the results.

Learn Top SAP MDG Interview Questions and Answers that help you grab high paying jobs


1. What are the main modules of SAP MDG?

Master data governance, Data consolidation, Governance, Information governance, Master data management are the primary modules of SAP Master Data Governance.

2. What is the role of SAP MDG architecture?

The main role of SAP MDG architecture is to enable users to know about the workflow and processes that are involved in the process. 

3. What is a 3-system architecture in SAP?

SAP R/3 has been one of SAP's main products, where R stands for RealTime and 3 refers to three-tier application architecture (Database,Application Server and Client). In the modern environment, the SAP R/3 system powers most businesses. This software was used by approximately 80% of the businesses.

MDG Architecture simplifies and connects all an organization's business transactions through real-time integration. Real-time integration ensures that any change or upgrade in one application causes the data in the other applications to be automatically modified or updated. The primary goal of R/3 Architecture is to provide a set of tightly coupled, major business applications.

4. What is the purpose of SAP MDG?

The main purpose of SAP Master Data Governance is to manage organizational data. It lays the groundwork for big data management and operationalizes your data to optimize business benefits. SAP MDG automates and accelerates maintenance and business operations. It also serves as a storehouse for all information. where data circulates within a circuit. The ERP system provides the data and it is adjusted and consolidated to meet the MDG. Data addition and changes are made here, and the data is still distributed via Process Integration (PI).

5. What is the difference between ECC and MDG in SAP?

A major difference between ECC and MDG in SAP is DQM is only available in SAP. There are several other functions that are available on SAP but not on ECC. 

6. What is SAP MDG data model?

SAP Master Data Governance or SAP MDG model enables business to consolidate and govern master data. Master data is shared across an enterprise to run different business operations, add meaning to transactions and manage and maintain unstructured enterprise data and metadata.

7. What are the 3 pillars of MDG?

Priorities, policies, and processes are three pillars of Master Data Governance.

8. What are the key components of data modelling in MDG?

Entities, attributes, connections, & hierarchies are the key components of data modelling in SAP MDG. These components are used to provide a logical model of master data, specify the relationships that exist between the various entities, organize data in a hierarchical structure, and manage it.

9. What are the different types of entities in SAP MDG?

SAP MDG supports key master data entities such as material master, business partner, customer master, supplier master, contract accounts receivable and payable (FI-CA), internal orders, and finance master data objects such as general ledger accounts, cost centre, profit centre, and so on.

10. How many types of MDG deployment is there?

There are two types of SAP MDG deployment - co-deployment and hub deployment.


It is critical to maintain data quality to achieve the overall performance of any business application. In this SAP Master Data Governance article, we understood the functions, concepts, and purpose of SAP MDG architecture, its overview, key abilities, business functionalities, and applications of SAP MDG in various enterprises. Learning this article may help you to explore more about SAP Master Data Governance which ensures the high-level data quality management system.

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Last updated: 14 Nov 2023
About Author

Kalla Saikumar is a technology expert and is currently working as a Marketing Analyst at MindMajix. Write articles on multiple platforms such as Tableau, PowerBi, Business Analysis, SQL Server, MySQL, Oracle, and other courses. And you can join him on LinkedIn and Twitter.

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