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Master Data Quality Management with SAP Master Data Governance on SAP S/4HANA 1909

With the latest release of SAP S/4HANA 1909, SAP Master Data Governance received a comprehensive update of the data quality management capabilities that were already introduced with SAP S/4HANA 1809.


  • Data quality evaluation to measure and analyze the quality of existing master data.
  • Business Partner (including customer and vendor), Product, and customer-defined objects supported. Support of further domains by Solution Extensions to be announced.
  • Rule mining applies machine learning to discover rules in existing master data.
  • Validation of data in change request processing with the same rules used for data quality evaluation.

Rule Management

Collaboratively describe, catalog, and implement rules for data quality using a central rule repository

The rule repository of MDG allows you to manage your rules for master data quality in one single place. It provides you with a repository to catalog and define data-quality rules, including comprehensive descriptions of rules, business aspects, and contact information. Various statuses of rules and collaboration features, for example using SAP CoPilot, allow you to handle the complete lifecycle of rules. Furthermore, the implementation of rules in BRFplus is also done from this app. This gives you full transparency on business aspects, usages and the technical implementations of all rules.

Rule Mining

Discover new data quality rules utilizing machine learning, analyzing your existing data

Besides entering already known data quality rules, data and business specialists can use mining runs to apply machine learning on existing master data. This will analyze how various aspects of the master data relate to each other and propose rules. The specialists can then collaboratively decide on the business relevancy of the proposed rules. Once accepted, data quality rules can be automatically created, including the transfer of the detected insights to the implementation of the data quality rule. Rule mining eases and shortens the discovery of rules and makes the qualification and implementation of data quality rules more efficient.

See also what Kefeng Wang writes in his blog Using MDG Rule Mining to Improve Data Quality for more information!

Data Quality Evaluation

Assess data quality by applying data quality rules on existing data

Data quality evaluation applies all rules to the active data in the system. The results of the evaluation are stored for later analysis. You can initiate evaluations ad-hoc, but of course also schedule evaluations, for example at weekly intervals.

Data Quality Analysis

Monitor progress of data quality initiatives and get insights for improvement

During data quality evaluation, the system stores the outcomes when applying the rules to your data. Furthermore, scores are calculated for each rule that indicate the share of good data in your system. You can group multiple rules in data quality dimensions. Data quality dimensions themselves belong to a data quality category. This allow you to define how you want to aggregate the scores on rule-level into higher-level KPIs for data quality reporting. You are provided with overview pages to monitor the current data quality situation and report on its trend. From each report you can drill-down to the lower-levels of your definition of data quality to identify root-causes of bad data.

Data Quality Remediation

Efficiently delegate or perform the remediation of data quality issues

Of course, you want to fix the issues in your data, once the data quality evaluation has detected it. From within the apps for data quality analysis, you can

  • Directly fix single products or business partners by opening any of the apps assigned to you, for example Manage Business Partner Master Data.
  • Delegate the correction to somebody else by sending the results of your analysis as a link to the app including filters and other settings.
  • You can export the evaluation results in open office (XLSX) format.
  • You can fix multiple products or business partners with MDG’s powerful mass processing capabilities.
  • You can export selected business partners or products in open office (XLSX) format for offline editing and later import in the MDG mass processing app

Check of Data in Change Requests

Apply data quality rules at the point of data entry with central governance

With SAP S/4HANA 1909 you can use the same data quality rules for quality evaluation and for check in change request processing. This makes the definition process of rules efficient, as you only have to create a rule once. It also caters for consistent application and implementation of rules for both data quality evaluation and data entry. Please note that with the initial shipment of SAP S/4HANA 1909 this feature is only available for business partner master data (MDG-C, MDG-S, MDG-BP). We plan the availability for MDG-M with the next feature pack.


With SAP S/4HANA 1909, master data quality management with SAP MDG is not only available for product master data, but also for business partner data. Further domains are planned to be covered with solution extensions.


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
  • Re-use of rule definition and implementation for the purpose of data quality evaluation and check of data during entry with MDG’s change requests.
  • 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 pre-defined master data models, 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

Further Information

What’s New in Data Quality Management with SAP Master Data Governance on SAP S/4HANA 1909 (PPT)

Webinar recording featuring the new features of Data Quality Management with SAP Master Data Governance on SAP S/4HANA 1909

Documentation of configuration and usage – Visit and make sure that you selected the S/4HANA 1909 version. Then navigate to Product Assistance -> Cross Components -> Master Data Governance. See the respective sections on Rule Management and Quality Evaluation beneath the nodes Configuration of MDG, Data Quality Management and Working with MDG, Data Quality Management.


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  • Love the potential of these tools in a true MDG Governance Deployment Model. I am working on value matrix to help with business case and value realization concepts. Ask me about an MDG Charter.

  • This is real promising. In today's world we have to use tools like Info steward for Data quality. what is the plan from SAP to get the Finance master data domain included as well. Based on different artifacts looks like these Apps are available only for BP, C, V and Material. How do we leverage these capabilities for FI data.

    • Hi Ravi,

      yes you are right: availability is for the product and business partner domains, plus custom objects (if based on re-use active area, and not flex entities). We currently think about how to address the requirements for FI data the best way, but it is too early for any statements. Right now, checks for FI data can be done with the BRFplus functionality available a part of MDG change request processing. see Definition of Validations and Derivations in BRFplus

      Kind regards

  • Hi Andreas,

    Thank you for sharing. This is a great addition to SAP MDG.

    Is it possible to import rules into the DQM rule library (with an excel file or with any other method)?.

    We have several data quality rules built-in Data Services and Information steward - and we would like to use them in MDG DQM. I'm sure it won't be straight forward export from IS and import into DQM as DQM uses the BRF+ rule framework and IS is not.

    Thanks in advance.

  • Hi Andreas,

    Can we used these data quality rules on source data during consolidation process for e,g, in validation step ?

    Used to assess data quality (data profiling) before loading data to active area ?



    Anurag Verma

  • This is indeed a great addition to MDG S/4 HANA capabilities . For customers who are on previous S/4 HANA versions like 1709 - how to tap into MDG DQM functionality ? Do we have to upgrade the or S/4 HANA 1709 to 1909 ?

  • Hi Andreas,  Trying to Import rules via Import Data Quality Rules for Product app, but selecting Start validation button, Status changes to Validation Error, checked for any missing auth as well but no errors. Mainly No error details found in the Log as well.

    Kindly advice, how to check this error? We are in S/4 1909 FP S01.


    Import Rule - validation Error




    • Hi,

      if the app does not give you information to find the issue and you checked already SU53 and SLG1: please create a support incident.

      Kind regards

  • Hello Andread,

    Hope you are doing well & Safe.

    Could you please advise for the below points :

    1. Can we enable this for S/4 hana release 1909 ?
    2. Can use this data quality for MDG-F (Finance Objects like GL,CC,PC,Others), if yes there any defined document/post to refer ?


    Sameet Kumar