A data quality solution architecture based on knowledge
A data quality, data technology, applied in the field of knowledge-based data quality solutions, can solve problems such as inability to solve data association, unresolved, low data quality, etc.
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[0030] Data quality deficiencies can have a negative (sometimes significantly negative) impact on business strategy measures. The effects of data quality deficiencies (eg, low-quality data) include: additional time spent correcting data (if errors are discovered), loss of credit, customer dissatisfaction, compliance issues, and lost revenue, among other effects. As a result, organizations of all kinds seek to improve the quality of their business data. General approaches to data quality (eg, based on zero-knowledge) are insufficient to produce high-quality data for today's business. Furthermore, knowledge-based approaches to data quality can present various challenges such as knowledge acquisition, usage, mobility, scalability, and more.
[0031] Thus, it would be beneficial to provide a knowledge-based approach to data quality through the separation of acquiring knowledge and processing knowledge to improve data quality. In an example, gathering knowledge...
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