Research On Metadata-based Data Quality Control And Assessment Model

The data, as the enterprise's asset, whose quality determines the level of the value of those assets. Data quality is a common problem, but also the inevitable problem. So, how to provide high-quality data for enterprise decision-making has been the key obstacle to enterprise development.For the poor data situation caused by large quantities, wide range of type and professional. In this thesis, a model as metadata-based data quality control and assessment is proposed , which focuses on the data of data center and based on theory of metadata, data quality and data model, study carefully the cause of data quality problems arising, quality inspection, quality control and quality assessment in the data flow. This model reflects the idea of all data quality management that distributed the factors of affect the quality of the data to the several stages: the quality of data dictionary, constraint rule in schema, constraint rule in instance and the data quality assessment criteria. If we can control the quality of those stages mentioned above,then the data quality of enterprise will be obtain a powerful guarantee .In this thesis, we construct the data dictionary for business data of data center to control the metadata from the beginning of modeling, and construct the data quality definition model from integrity, consistency, accuracy and timeliness of data based on the quality status of existing data. At the same time,we define the constraint rules in schema and instance to control and assess the quality of the data. It achieves all control for data by different metadata for each link that data quality problems may occur to improve the quality of the data.Finally, this thesis, we implement software, which can control and assessment data quality by meta-data, and applied preliminarily to the project of data center, the results show that good efficiency and operating results.