Data quality-based grassroots governance digital checking index evaluation method

Abstract

The invention discloses a data quality-based grassroots governance digital checking index evaluation method. The method comprises the following steps of: 1, investigating the current situation of data; 2, determining a data management range; 3, formulating a data management standard; 4, establishing a business model; 5, aggregating data; 6, establishing a data quality checking index; 7, evaluating the data timeliness; 8, evaluating the data completeness; 9, evaluating the data integrity; 10, evaluating the data consistency; 11, evaluating the validity of the data; 12, evaluating the data repeatability; 13, processing data source; and 14, storing data in database. According to the method, the ambiguity of data definition can be reduced, the classification of total elements is realized, the usability of data is ensured, and the whole-process, full-time, full-coverage and omnibearing management can be realized; and meanwhile, multi-party data resources are fused and collided, so that the data use value is greatly improved.

Description

technical field [0001] The invention relates to a data quality-based digital verification index evaluation method for grassroots governance. Background technique [0002] Grass-roots governance is the micro-foundation of national governance and city governance, and an important cornerstone of the national governance system. At present, the following deficiencies exist in the grassroots governance process: [0003] First, different government departments build different business systems, leading to the problems of repeated construction of information platforms, scattered and closed data in grassroots communities. In this way, there are many data sources but lack of unified data standards, which not only consumes a lot of resources at the grassroots level, but also makes grassroots governance difficult, and it is impossible to quickly realize closed-loop management, resulting in unclear grassroots management, incidents, and family background. [0004] Second, the business sy...

AI Technical Summary

Problems solved by technology

Because the vertical management departments ask for data from the grassroots, the contents of the forms issued by many departments are basically the same, but the format and style are slightly different. increased workload;

[0005] Third, the traditional business system does not consider data quality issues, resulting in low overall data quality in the business system, lack of data quality-oriented evaluation mechanisms and data quality evaluation methods, resulting in inaccurate, untimely and contradictory data, etc. Delayed service efficiency of various government departments

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