Abstract
Data quality issues are exacerbated when information is distributed across heterogeneous siloes data stores throughout the organization. The nature of this environment usually involves an architecture of values that conflicts with various formats. Even within a single database, consistent data quality is not always good unless appropriate rules are applied. Whether the information is dormant in the data warehouse or manipulated quickly by the application, the data quality is not enforced at all or is controlled by various components with inconsistent rules embedded in the code. To turn information into knowledge and harness its great value, data quality must, of course, be addressed through the application of continuous data processing, starting with proper and systematic evaluation. Therefore, using hard rules across the enterprise, not only at the database level but also at the application and process level, can help deliver services and improve customer satisfaction.
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Lubis, M., Raafi, E., Prayogo, S. (2023). Beyond Data Quality: The Assessment of Data Utilization in Indonesian Telecommunication Industry. In: Nagar, A.K., Singh Jat, D., Mishra, D.K., Joshi, A. (eds) Intelligent Sustainable Systems. Lecture Notes in Networks and Systems, vol 579. Springer, Singapore. https://doi.org/10.1007/978-981-19-7663-6_23
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