Research On The Application Of Big Data In Tax Governance In J District Of Changzhou City

In recent years,with the rise and application of big data,tax authorities at all levels have been actively committed to the construction of "managing taxes with numbers".The transparency,efficiency,and predictability of big data have provided strong technical support for tax governance work,especially in solving various information asymmetry between taxpayers and taxpayers,strengthening tax risk prevention and control,and improving the overall service level of taxes and fees.Therefore,the tax department takes tax big data as a cutting edge,and through deep mining and application of big data,further improving the comprehensive level of tax governance has strong practical significance.This article takes J District of Changzhou City as the research object,starting from the theoretical perspective of big data and tax governance,introduces the development background of big data in recent years,and summarizes the research of Chinese and foreign scholars on big data,tax governance,and the application of big data in tax governance.In response to the current situation of tax governance in J District of Changzhou City,a thorough analysis was conducted on the data barriers that are difficult to break through in the process of using big data for tax governance,the tax governance model lags behind actual needs,data security risks need to be eliminated urgently,weak data analysis and mining technology,mismatch between human resources and tax governance needs,and other issues.By using literature research,questionnaire survey,interview methods,and other methods to address the causes of the problem,and combining with specific practical situations,suggestions have been proposed to solve the problem of big data application in tax governance in J District of Changzhou City.These suggestions include establishing big data tax governance thinking and concepts,consolidating the basic environment for big data application,improving tax organizational structure and optimizing talent teams,ensuring the security of tax big data,and improving tax governance efficiency.