Therefore, for digital transformation enterprises, tracing data sources, unifying data definitions, classifying data storage, and eliminating invalid data can reduce data management costs, avoid legal risks in data application, and reduce product maintenance and development costs. So how should data be properly Slovenia Phone Number governed? 1. Organize business rules and unify data definitions A common Slovenia Phone Number understanding and interpretation of data is critical in the digital transformation of an enterprise. Data quality issues usually refer to the same dataset being interpreted as different things, or different datasets being interpreted as the same thing.
Whether it is business or technical metadata, clear data definition based on business attributes is very important to improve data quality. Enterprises can make data governance teams use certain data management applications to sort out business rules and unify data definitions . 2. Track external data sources In the Slovenia Phone Number face of the fiercely competitive market environment, the direction of enterprise data application is no longer limited to internal data, but more focused on Slovenia Phone Number third-party data, which has become one of the elements that constitute an analysis solution. Whether it is partner data, supplier data or Internet open data, it can enhance the resources of enterprises to obtain new business value.