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With the latest release of SAP S/4HANA 1809, SAP Master Data Governance offers comprehensive data quality management capabilities for product master data.

Data Quality Rules

This new app provides you with a repository to catalog and define data-quality rules. You can describe your rules comprehensively, including business aspects, ownership information, and their implementations. Life-cycle management is supported by status handling and various collaboration features.

Measure Data Quality

The data quality rules can be applied to all product master data in your SAP S/4HANA system to provide a one-time or scheduled evaluation, for example at regular intervals. This provides you not only with a snapshot of the current findings on the level of each product and rule. You can decide how long to keep these results, so you can observe trends and deltas over time. Rules can be assigned to freely defined data quality dimensions and weighted according to their impact to provide you with data quality scores.

Analyze Data Quality

The evaluation result can be analyzed using attributes of product master data and data quality rules, so that you can manage your data quality initiatives and prioritize your efforts according to impact and business value.

Correction of Data Quality Issues

Core editing capabilities of SAP S/4HANA, as well as extended features provided by SAP Master Data Governance for governance of product master data, are integrated with the data quality analysis to efficiently fix errors.

Data Quality Overview

Data quality information at a glance is provided in one single place, where you can see the current data quality score, it’s trend over time and the distribution of errors in your product master data along multiple dimensions. From this overview page you can drill-down to the actual evaluation result on the level of products and rules.


Master Data Quality Management with SAP Master Data Governance provides you with unique benefits:

  • A central repository for data quality rules, striving to cover every master data process in SAP Master Data Governance
  • With a few configuration steps (link and no development at all you are ready to go with data quality management that is embedded into SAP Master Data Governance and SAP S/4HANA.
  • An easy way for rule implementation, based on the pre-defined product master data model, including for example value helps, plus the strengths of the BRFplus workbench and the robustness of its execution runtime
  • All data quality capabilities are accessible via the SAP Fiori Launchpad, making them available to all stakeholders in your organization embedded in their regular SAP S/4HANA work environment.
  • The possibility to drill-down from high-level KPIs, down to direct access to active master data in one single place, benefiting from the integration into SAP S/4HANA, for example due to the re-use of application authorizations when analyzing evaluation results.
  • Insight-to-action from where you analyze data quality findings to actually correct detected errors

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  1. Ali Ansari

    Great blog Andreas! Thank you for sharing.

    The slides from the presentation link you shared say that DQM is not planned for MDG on ERP.

    So is S4/HANA 1809 the only way to consume Master Data Quality Management or will it be available in the future on SAP Cloud Platform?



    1. Andreas Seifried
      Post author

      Hi Ali!

      Thanks for the kudos.

      There are no plans to make this available for MDG on ERP. Like more and more innovations we will only ship this as part of S/4HANA.

      Comparing master data quality management like described above with a potential SCP-based offering: Which differences and benefits would you expect?

      Best regards


  2. Ali Ansari

    Hi Andreas,

    My thoughts initially were instinctive as a developer. To get my hands on a trial version of a SCP service to explore and experiment would take considerably less time rather than to wait for the latest S4 release to reach me.

    The major benefit I would expect from master data quality management as a cloud offering would be it’s capability to point out bad data and demand a need for MDG.

    Initial Data assessments powered by data evaluation, measuring data quality, analyzing data quality topped off by a complete data quality overview. All points which you spoke about in your blog, required way before customers sign off on MDG or even S4.

    Best Regards,


    1. Andreas Seifried
      Post author


      Hi Ali,

      thanks for sharing your thoughts!

      Short time-to-value is certainly a generic benefit of a cloud-based offering. I also agree to the lifecycle aspect: invest into defining what your data quality standards are, then first make a DQ assessment, after that do the clean-up work and go into continuous operations.

      Well, let’s see what we can do, but this is certainly nothing around the next corner 😉



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