What best practices should be followed for data distribution in MDG?

The best practice for data distribution in SAP Master Data Governance emphasizes the necessity of accurate validation before the data is shared with stakeholders. Ensuring that data is validated means confirming its accuracy, completeness, and consistency, which is crucial for maintaining the integrity of the master data. When data is validated, it minimizes the risk of distributing incorrect or misleading information, which can lead to poor decision-making and operational inefficiencies.

In the context of MDG, the core principle is to provide trustworthy and reliable data to the organization. When stakeholders receive validated data, they can be confident that the information can be used for business processes, reporting, and analytics effectively.

Data distribution based on user preferences may seem user-centric but does not guarantee the quality of the data being distributed. Automatic distribution without validations poses significant risks as it could lead to spreading erroneous data. Relying solely on historical data trends overlooks the importance of current data accuracy and does not align with the principles of Master Data Governance, which aims for real-time accuracy and reliability. Therefore, validating data before distribution is an essential practice to uphold the standards of data governance.