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A data steward is a role that ensures that data governance processes are followed and that guidelines are enforced, and recommends improvements to data governance processes. Data governance involves the coordination of people, processes, and information technology necessary to ensure consistent and proper management of an organization's data ...
A data steward ensures that each assigned data element: Has clear and unambiguous data element definition; Does not conflict with other data elements in the metadata registry (removes duplicates, overlap etc.) Has clear enumerated value definitions if it is of type Code; Is still being used (remove unused data elements)
In data governance groups, responsibilities for data management are increasingly divided between the business process owners and information technology (IT) departments. Two functional titles commonly used for these roles are data steward and data custodian .
However, data has to be of high quality to be used as a business asset for creating a competitive advantage. Therefore, data governance is a critical element of data collection and analysis since it determines the quality of data while integrity constraints guarantee the reliability of information collected from data sources.
The Data Owner is responsible for the requirements for data quality, data security, etc. as well as for compliance with data governance and data management procedures. The Data Owner should also be funding improvement projects in case of deviations from the requirements.
All data having attributes referring to Reference Data in the organization may be validated against the set of well-defined valid values of Reference Data to discover new or discrepant values through the validity DQ check. Results may be used to update Reference Data administered under Master Data Management (MDM).
The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing. I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (Meta)data use vocabularies that follow FAIR principles I3.
The datasphere is a multidisciplinary concept that first appeared in the 1980s. While many terms have been adopted to describe the digital world – terms such as the Internet, cyberspace, metaverse – the various concepts of the datasphere seem to address the growing dependency of human activities on data, as well as approach the digital world in a holistic manner.