Managing Metadata in Data Warehouse for Data Quality and Data Stewardship in Telecom Industry - A Compact Survey

Managing Metadata in Data Warehouse for Data Quality and Data Stewardship in Telecom Industry - A Compact Survey

연구 분야: Databases

학회: 2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)

Present telecom industry database provided poor data quality, specifically metadata quality. As a result, decision making data are missing for analyses. Metadata may contain information about the schema of the data so that the data can be transformed into quarriable data objects when required. The data warehouses (DWH) acceptance has grown hugely for data analysis. The main part of data warehouse includes source of data, software for data acquisition, repository, tools for data analysis, and user interface. So many factors are responsible and be critical for DWH successful implementation, they are type of organization, sufficient technical information, project type, work environment, infrastructure, quality of information, quality of system, quality of Service, and quality of relationship. For data quality and its analysis, metadata, and its roles that metadata plays are very important for organization. Metadata management is a central part of the data analysis process. Metadata carries information about data schema that helps to transformed into quarriable data objects when required. For all projects related to data warehouse, the most important factor is metadata. It catches all types of necessary information to design, simplify, build, and use the data warehouse which contains project related data. Functions of metadata system are to collect and store information in single place, which provides an overview for metadata, such as searches, queries, create, maintain, evaluate and managing access of metadata by establishing role-based security. Stewarding metadata is important for the application of data governance practice for enterprise to provide the value and the context for explaining the data and its components to the end users. With the help of the metadata concepts, the organizations can define a business rule for the specific data attribute.