China 
Africa 
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The three-axis approach to analytics projects
Published in Ondřej Bothe, Ondřej Kubera, David Bednář, Martin Potančok, Ota Novotný, Data Analytics Initiatives, 2022
Ondřej Bothe, Ondřej Kubera, David Bednář, Martin Potančok, Ota Novotný
Business metadata (e.g., the business meaning of a given attribute) will be needed almost for any project (though not for all the people participating in the project) as analysts will need a business understanding of the data used for data integrations or analytical calculations. The need for a higher level of governance will increase with the number of metadata, the number of consumers and more robust projects. What if the business description of the data is not available yet? Acquiring this information needs to be planned for, and we need to ensure the cooperation of the subject matter expert (likely the data steward).
Data Governance Model To Enhance Data Quality In Financial Institutions
Published in Information Systems Management, 2023
The business data dictionary manages both business and technical metadata. The Data Governance Model introduces business metadata as a business definition of business terms/KPIs, a list of applications that serves as a data source for KPIs, a list of reports where KPI is used, and roles management. Each KPI has assigned its respective business-term owner and data stewards. KPI definition contains its calculation formula. The calculation formula is mapped to the data source or various data sources based on which the KPI is calculated. These data are considered as critical data elements. Each data has been assigned to its respective data owner and delegated data stewards. The data source is defined in an application catalog, which can be part of the business data dictionary. For each application, the create, read, update, and delete (CRUD) matrix is defined to have awareness of the basic operations to be done in the data repository for the respective data dimension. Each application has an assigned business system owner.