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MDQ

Master data quality ensures that enterprise master data is correct, complete, and consistent.
With clear rules, automated checks, and suitable governance, MDQ supports efficient processes and reliable reports.
Clean master data form the foundation for robust process flows, lower risks, and sustained business success.

What is MDQ?

Master data quality (MDQ) (in the SAP context) is the term for the systematic assurance that master data is complete, correct, consistent, up to date, and, suitable.
Master data represents key business data such as customers, suppliers, materials, products, company codes, charts of accounts, and many other objects that are used in many SAP modules (such as FI, MM, SD, and PP).

A high level of master data quality is decisive for correct processes, reliable reports, and automated process flows. SAP offers its own solution for this: SAP DQM (Data Quality Management). It belongs to SAP MDG. Master data quality can also be achieved through other technical and organizational means, however, using SAP DQM is not a mandatory requirement for master data quality.

How does MDQ work?

Master data quality (MDQ) works through the interaction of rules, processes, responsibilities, and technology, to ensure that master data remains clean, complete, and consistent.

There are four core modules for this:

  • Data rules and standards
  • Validations and quality checks
  • Governance and roles
  • Monitoring and continuous improvement

What are the advantages of using MDQ?

  • More robust and more efficient business processes
  • Higher level of data quality in analyses and reports
  • Lower costs
  • Fewer risks and compliance violations
  • Serves as the foundation for automation and digitalization
  • Avoids duplicate records
  • Improved collaboration between departments

What are the disadvantages of using MDQ?

  • High initial effort
  • Investments in technology and tools
  • Need for the organization to change
  • Additional process steps
  • Dependency on data owners
  • Ongoing maintenance effort
  • Complexity when many systems are involved

What are the essentials of MDQ?

It is especially important for MDQ to ensure clear rules, clear responsibilities, automated validations, and ongoing monitoring.

This is the only way to ensure that data quality will remain robust and effective in the long term.

  • Define clear data standards
  • Define data ownership
  • Use automated validations
  • Consistent processes for master data maintenance
  • Continual monitoring
  • Train the specialist departments and promote awareness for data quality as an enterprise value
  • Integration across all systems

What is the difference between MDQ, MDM, and MDG?

The terms Master Data Quality (MDQ), Master Data Management (MDM), and Master Data Governance (MDG) are directly related.

To put it simply, master data quality is the goal you want to reach. This quality is achieved through consistent, clearly regulated master data management, which describes all the technical and organizational measures for master data maintenance. In turn, the underlying rules that ensure this are described as master data governance, which defines responsibilities and rules for the definition and management of master data.

Should businesses pursue MDQ?

Yes, master data quality (MDQ) as a clearly defined target vision is essential for businesses.
It’s not a “nice to have”; it’s a strategic prerequisite for robust SAP processes, a high level of automation, and successful digitalization. Master data quality is the goal by which all master data processes must be measured.

SAP provides a mature MDQ framework in MDG, in the form of the DQM features – you can potentially use this tool to achieve and measure master data quality.

What is the right way to use MDQ?

MDQ is not a single tool; it is a continual, process-driven approach to ensuring sustained data quality.
It only works through the interaction of clear rules, defined responsibilities, automated quality checks, and standardized maintenance processes.
Regular monitoring and ongoing improvements are decisive elements, because MDQ is an ongoing quality process, not a one-time cleansing.

Is getting started with the topic of MDQ recommended?

Getting started with MDQ management is clearly recommended, because modern SAP processes, automation, and SAP S/4HANA require clean, consistent master data.
Without MDQ, error rates, manual post processing, and project-related risks will increase significantly, while MDQ will give a big boost to efficiency, stability, and scalability.
In short: MDQ is practically essential for today’s SAP landscapes – organizationally, technically, and economically.

How does MDQ help in everyday business?

MDQ helps with your everyday business by preventing errors in master data, making processes more robust, and reducing manual postprocessing.
As a result, SAP process flows like purchase orders, bookings, and deliveries will run more smoothly and more reliably.
In other words, less chaos, fewer corrections, and greater efficiency.

Who can support me with MDQ?

gicom offers extensive expertise for all central master data topics in the SAP context.

What tips can you provide for MDQ?

  • Define clear rules
  • Use automated checks
  • Define responsibilities
  • Standardize maintenance processes
  • Measure data quality regularly
  • Provide training and raise awareness
  • See mistakes as an opportunity: sustained improvement instead of putting out fires.