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Author's profile photo Ina Felsheim

Data Quality Metrics and KPIs: How to Present Them?

This blog highlights an ASUG webinar done by Decision First’s Rich Hauser (@richhauser). For more details, check out the Decision First blog.

This session highlights best practices on not only creating data quality scorecards, but also how to use your SAP Business Analytics tools to get extended visualizations out of SAP Information Steward —visualizations that really pack a punch. The webcast includes a live demo. To get the live demo, however, you’ll have to register for the ASUG session and watch the recording (ASUG log-in required).

What visualizations come with the EIM software?       

Data Quality visualizations and monitoring, and consists of the following levels of aggregation:

  • Key Data Domains (customizable)
    • Quality Dimensions (customizable)
      • Rules (customizable)
        • Rule Bindings

All of this information is used to construct a scorecard. The good news is that you can either just auto-weight everything equally, or you can customize the weighting of scores to give higher impact to some specific areas.

Historical scores are stored in the Information Steward repository for:

  • Tables
  • Views
  • Columns that are bound by at least one rule
  • Rule bindings
  • Quality dimensions
  • Key data domains

We can use this data from the repo to visualize data quality scores in many different ways.

Other EIM Data Quality visualizations

Information Steward also provides validation rule results, profiling results, and rule task results. There are also some data quality reports in SAP Data Services—check the Data Services Management Console. Be aware that you can create additional, extended reports using the status codes and assignment codes (including the descriptions).

Status codes and alignment codes can tell a story, providing granular detail about what exactly was improved.

Drill-able visualizations are also available in the Data Quality Advisor inside of Information Steward, but are used during creation of the data quality rules. The following brings together some of the quality rules into a visualization.


What are good ways to extend these visualizations?

To really understand how to create visualizations on top of Information Steward, you must understand the Data Services and Data Quality and Information Steward process chain. Rich advised to use the Information Steward repository as a data source inside of Data Services, as it is sometimes easier than creating a universe.


These are the primary Information Steward repository views that are useful for extended reporting:

  • MMB_Key_Data_Domain
  • MMB_Key_Data_Domain_Score
  • MMB_Key_Data_Domain_Score_Type (Key Data Domain, Quality Dimension, or Rule level)
  • MMB_Domain_Value (Quality Dimension descriptions)
  • MMB_Rule (Rule definition/description)
  • MMB_Data_Group (Project Names)

For more information, reach out to @richhauser.

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