A Noval Data Quality Controlling and Assessing Model Based on Rules

As a resource, data is the base for information construction and application. According to the principle of “garbage in and garbage out”, it needs us to ensure data reliability, no errors and accurately reflect the real situation to support the right decisions. However, due to various reasons, it leads to poor quality of dirty data in existing system business, while the dirty data is an important factor which affects right decisions. For the above, in this paper, a metadata-based data quality rule base is created for improving traditional quality control model, a more practical application of the weighted assessment algorithm is proposed and a three-tier data quality assessment system model is constructed based on the study of definition and classification of quality, assessment algorithm, metadata and the control theory. This model is confirmed to achieve comprehensive quality of data management and control in oilfield practical applications.