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Why Master data governance we have to use in industries
December 13, 2021

Why Master data governance we have to use in industries

Sachin Jagtap | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with SAP Master Data Governance

Sap Master data governance (SAP MDG), central government provides central ownership of master data in line with a company's business rules and processes. MDG delivers the domain-specific, out-of-the-box application as well as a framework for custom-defined master data. MDG can be deployed as a separate hub system or co-deployed with sap ERP. In both cases, and can use SAP and company-specific business logic to create master data ready to be used in a company's business processes. In our organization, we develop SAP EAM solution which is used in many organisations and companies. In retail, fashion, Artificial intelligence, machine learning, and many more domains we are thinking to develop in MDG.
  • Retail and fashion.
  • MDG Enterprise Asset management (EAM).
  • MDG Asset information Workbench (AIW).
  • uDGA - utopia data Governance Accelerator tool.
  • uBIPS, uXloader, uTaxonomy,uDQR, uDM.
  • Artificial intelligence.
  • Machine learning.
  • Fiori.
  • EAM - positive.
  • Sap MDG for retail and Fashion management- positive.
  • Sap AIW - positive.
Every organization is different. There can be no universal one-size-fits-all framework for master data governance, although there are key elements that everyone must pay attention to. These include transparency, maintenance, data ownership, change management, compliance, accountability, authority, auditability, data stewardship, standardization, and education. Many proponents of data governance have fixed models which have been proved to work in previous engagements. The issue is that many of these fixed solutions disregard your organizational capabilities. Use the steps in this infographic as a starting point for your master data governance journey
Ensuring data definitions from the beginning can provide a high quality of data throughout the data lifecycle. That way, data stewards and data owners across the enterprise can work with accurate data. This is where MDG can help: by defining permissions and tasks for users at a granular level. Data collection, classification, and quality control must be applied before the implementation of a data governance framework. You need to have clear definitions of things like acquisition and accessibility in order to govern data, and these are essentials of MDG.

Do you think SAP Master Data Governance delivers good value for the price?

Yes

Are you happy with SAP Master Data Governance's feature set?

Yes

Did SAP Master Data Governance live up to sales and marketing promises?

Yes

Did implementation of SAP Master Data Governance go as expected?

Yes

Would you buy SAP Master Data Governance again?

Yes

Data governance is an enterprise-wide discipline with a vast purview. The picture of what data governance is getting easily muddled when you consider the many types of data: transactional data, behavioral data, performance data, temporal data, operational data, and many more. As an organization, we need a single customer view across multiple lines-of-business, for differing purposes. And those different purposes will raise questions as to the actual definition or meaning of ‘customer’. Master data governance allows a glossary of agreed terminology to be created along with particular metadata attributes which are used to define ‘customer’ and provide a standard and consistent definition across the organization. This reduces the scope for misinterpretation, misuse, confusion, and errors in the future.