The data quality of geographic national conditions monitoring affects the accuracy of data analysis and decision-making. This paper discusses the main problems existing in data quality from the aspects of data collection

processing

transmission

storage and use

analyzes the influencing factors of each link and puts forward the corresponding improvement methods. The accuracy and reliability of data collection are improved by combining multi-sensor data fusion technology. The consistency and integrity of data are ensured by optimizing outlier detection and data interpolation methods. The hash check code is adopted in data transmission and storage to ensure the integrity of data transmission. Based on the dynamic quality evaluation model

the practicability of data in different application scenarios is improved

and the effectiveness evaluation index system is constructed to verify the improvement method. The results show that the quality improvement method effectively improves the accuracy

integrity and consistency of data

and provides reliable support for relevant data analysis and decision making.