1. What is big data and what is the purpose of data application?

Big data can be simply understood as a collection of data with a particularly large number and a particularly large data category. It can be used for users to analyze different phenomena and problems according to different needs, and then draw conclusions through data integration and comparison. To sum up, the purpose of data application can mainly solve four problems: First, reflect the situation. Through the use of data, we can reflect the relevant situation of a person, a group, a class or the whole thing. This data application is characterized by simple sorting and calculation of data, and data processing has no special purpose and intention. The second is to find problems. According to experience, it is assumed that there may be some problems in things, and then the existence of the problems is verified by selecting certain data and adopting certain operation methods. For example, when we calculate and consider whether something may happen, we always design some indicators according to past experience to find problems. The third is to find the law. By comparing two or more groups of data in different periods, summarize the law and relationship of things' development. The fourth is to find trends. To observe the development trend of things, it is generally necessary to reflect the development or change trend through the numerical value of a certain data at different time points. Whether using data to reflect the situation, finding problems, or looking for laws and trends, the fundamental purpose is to strengthen management. Therefore, the essence of data application is a management activity.

Second, the meaning of tax collection and management

Tax collection and management is the management of the implementation and enforcement of tax policies, and it is all about some regulations on how to implement tax policies in concrete implementation, including tax registration, invoice, declaration, collection, tax refund, evaluation, inspection, illegal handling, reconsideration complaints, policy consultation and publicity, tax tickets, tax accounting analysis and so on. After the tax authorities separated the tax business in 2009, the current tax collection and management refers to tax supervision, whose main purpose is to prevent taxpayers from evading taxes or how to accurately find out the problems of tax evasion.

Third, how to link big data and tax collection and management, and how to optimize and improve tax collection and management.

First, accurately use data to reflect problems, find problems, find out laws and trends, and realize information-based tax management with the essence of data management, that is, use data for tax collection and management. In the process of tax collection and management, the tax authorities can compare the invoice issuing, business operation and tax declaration of enterprises in the same industry, scale and environment at the same time, and get the production and operation rules and development trends of ordinary enterprises. By comparing whether different enterprises differ too much from this law and deviate too much from reality, according to the data analysis, we can draw the conclusion that enterprises have problems such as false invoicing, so as to realize the purpose of tax collection and inspection. For example, compared with other enterprises in the same industry, the same period and the same scale, the tax authorities can quickly analyze whether there are problems in the operation of our enterprises. In this way, the application of tax burden level in the same industry intuitively reflects the application of big data in the combination of discovering laws and trends and tax collection and management, and realizes the information management of tax authorities. When the data information of different enterprises and different periods can be exchanged and cross-compared, it will become easier for tax authorities to realize tax collection and management when they find enterprise problems. Second, the application of big data eliminates the information asymmetry between tax authorities and taxpayers and helps tax authorities to realize tax collection. The application of tax data is mainly around how to define the tax source. The tax authorities have made clear the source of tax, realizing the information mastery of tax payers and the information symmetry between tax payers. As the tax department of the government, it is the bounden duty of the tax authorities to collect taxes. The highest goal of tax collection is to collect all accounts receivable. In order to recover all accounts receivable, the tax authorities must clarify the accounts receivable. The key to defining accounts receivable is to define the number of taxable households, and the statutory tax basis such as taxable income, taxable behavior and taxable property is the tax source. In tax work, taxpayers are required to register, receive invoices, declare and verify taxes, all in order to find out and master tax sources; Tax authorities collect taxes, conduct assessments, carry out inspections, punish and organize income, determine income tasks, analyze and forecast income, and conduct professional management, risk management and large enterprise management, all of which are based on tax sources. Therefore, in the application of data, no matter what the name of each job is, the tax sources are grasped from different angles and levels, some are macro tax sources, some are micro tax sources in the industry, and some are micro tax sources for evaluating and verifying specific households. Understanding tax sources is the basis of tax management and tax collection and management, and mastering tax sources is the main line of tax work, which runs through the whole process of tax collection and management and is the core cornerstone of tax work. Grasping the source of tax, we will grasp the root of tax revenue. Thirdly, the application of tax data mainly focuses on information management and professional management of tax sources, tax risk management and tax assessment. Key tax source management and large enterprise management, tax inspection and tax inspection, tax accounting and statistical accounting, detailed inquiry and comprehensive inquiry, tax economic analysis and income analysis and forecast, tax collection and management status analysis and quality evaluation, tax policy evaluation and law enforcement evaluation, task management and performance management. Some of the names of these data applications are traditional names, such as accounting and statistical accounting, analysis of collection and management status, evaluation of collection and management quality, etc., and some are new names proposed in recent years, such as professional management of tax sources, risk management, tax assessment and management of large enterprises, etc., which fundamentally promote the improvement of tax collection and management level.

Four, the future development direction of tax collection and data application

The development direction and path of tax collection and management is information tax management. The core is to use data to manage taxes, not to let the data lie there and sleep, but to let the data stand up and speak; Second, we should use information technology to make the data stand up. Whether the data is lying or standing ultimately depends on the application of information technology. Without information technology, the data will definitely be untenable. Without good information technology, data will either stand up or stand upright. Therefore, the key to future tax collection and management is dual-use, which is the only way to improve the level of tax management. The era of big data is an era full of opportunities and challenges. Tax collection and management should pay more attention to innovation and change, and truly let big data play its role and reflect its value. Tax authorities should also keep pace with the times, update their concepts and make changes in information system construction, data management, personnel training and application mechanism. Cultivate your ability to use big data, avoid empty talk about "big data" and really let big data shine.