Research On The Application Of Data Quality Management Methods For "smart Courts"

With the in-depth development of information technology,data has become one of the biggest sources of value for modern enterprises,and data quality management has become an important tool to support enterprise development strategy.It has become a key driving force for the development of enterprises to make rational use of the existing data to seek competitive advantage and to mine the useful information in the massive data.Data application is the basis of rational analysis and decision making.Improving data quality and using data to realize decision analysis play an important role in improving business efficiency and comprehensive competitive strength.At present,the value and potential of data assets are far from being explored.Once the data assets are in a state of chaos without governance,their importance will be reduced and their value will be greatly reduced.What's more,it will seriously affect the interests and decisions of enterprises.With the advent of the information age,data quality management has become more than a problem faced by the information department.The role of data quality management has gradually attracted the attention of major companies.Data quality management is a complex and arduous system engineering.The "Wisdom Court" aims to solve problems such as data "data island" effect and weak data analysis.In order to build a "Wisdom Court",data quality is crucial for data analysis,while for court data,its data quality is also facing various challenges.In order to solve the problem of court data,we put forward data quality management for courts.Data quality management can also be called data governance,which can be divided into data audit and data quality improvement according to functions.This paper is mainly around the data audit to expand.The specific content of this paper is as follows:1)put forward data quality management methods for "Wisdom Court" :Data quality management for "smart court" is divided into three steps:Step 1: make clear the data quality management objectives derived from the data of the people's high court of guizhou province,and analyze the existing civil case datainformation based on the application background of "Wisdom Court".The main problems are: data inconsistency,data missing,data irrationality and so on.Based on these problems,we use audit rules to audit them and propose data correctness Suggestions.Step 2: the general process and general technical method of data quality management are defined.The general process and general technical method of data quality management are summarized by studying many existing scientific research results.Step 3: put forward the applicable court data quality management methods,based on data has clear data quality management objectives and the conventional process of quality management,put forward the "Wisdom Court" oriented data quality management process,the process of data quality management of the conventional process of abstraction and generalization,to "Wisdom Court" as the background,according to the characteristics of court data to the data of quality management and refined the functions of the conventional process steps are steps cuts.2)design and implement the application platform of data quality management for "smart court" :Based on the proposed data quality management method and technical method for "smart court",this paper designs and implements the data quality management application platform for "Wisdom Court" through Hadoop,Spark,mysql,Postgresql,SpringBoot and many other mature big data technologies that meet the needs.In this paper,based on the implemented for "Wisdom Court" of data quality management application platform,the data of the guizhou provincial people's high court,the data quality management,and effectively solve the data inconsistency,data is not reasonable,made the problem of data visualization and may,according to court personnel requirements for flexible use of configuration data detection rules,according to the rules of audit on the label put forward a set of data quality assessment program to assess data quality issues.