On release SAP S/4HANA 2023FSP2 and Cloud 2408, SAP Master Data Governance has delivered data quality analytics 2.0, which enables end users, from Chief Data Officer to master data specialist, a real time quality abstract, and the data quality drill down. It includes 14 Analytics CDS views for product and business partners and 2 out-of-box data quality dashboards for product and business partners in SAP Analytics Cloud by leveraging these analytics CDS views.
Highlights:
Data Quality Analytics 2.0 provides Quality Score on dimensions for example, master data attribute, organization unit etc., used in the dashboard. It gives you a clear comparison between organization units for example plant, company code etc., on same data quality standard. Each Plant, Sales Org, Region owner have clear picture of their own data quality status and ranking among all organizations. From there, they are motivated to identify a problem, dig root cause, and finally put it into action to improve data quality. From aggregated data quality score, it is also possible to drill-down into each erroneous master data to trigger data remediation process.
On release SAP S/4HANA 2023FSP2 and Cloud 2408, SAP Master Data Governance has delivered data quality analytics 2.0, which enables end users, from Chief Data Officer to master data specialist, a real time quality abstract, and the data quality drill down. It includes 14 Analytics CDS views for product and business partners and 2 out-of-box data quality dashboards for product and business partners in SAP Analytics Cloud by leveraging these analytics CDS views.Highlights:Data Quality Analytics 2.0 provides Quality Score on dimensions for example, master data attribute, organization unit etc., used in the dashboard. It gives you a clear comparison between organization units for example plant, company code etc., on same data quality standard. Each Plant, Sales Org, Region owner have clear picture of their own data quality status and ranking among all organizations. From there, they are motivated to identify a problem, dig root cause, and finally put it into action to improve data quality. From aggregated data quality score, it is also possible to drill-down into each erroneous master data to trigger data remediation process. Read More Technology Blogs by SAP articles
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