Research On Data Asset Evaluation Model Based On Analytic Hierarchy Process

With the penetration of new technologies such as big data,cloud computing,and the Internet of Things into the lives of the people,human interactions and lifestyles have undergone a strong transformation,and the amount of valuable data has ushered in rapid growth.The deep integration between the big data industry and China's old industries and technological improvements can promote innovation in the social business climate,drive traditional industries to informatization,technology,and intelligent development,accelerate the transformation and upgrading of tourism and manufacturing industries,and stimulate new economic growth.To improve the competitiveness of traditional industries,reform scientific research,education and security models,enhance industry barriers,and enhance industry competitiveness.The application characteristics of big data are widely recognized by various industries,but the characteristics of assets have yet to be tapped.At the same time,domestic research on data assets assessment is indeed lacking,and related major research results are also evaluated in the value of intangible assets.Therefore,the research on the value evaluation of data assets in this paper has rich theoretical and practical significance.Foreign scholars have relatively mature research on the concept of big data and fully recognize the positive effect of big data on the development of various industries.For the evaluation of data assets,the theoretical research mainly focuses on the similar directions of valuation of intangible assets,evaluation of information assets,and assessment of network data resources,and studies the characteristics of intangible assets,information assets management process,and data asset value.The theoretical content of the assessment.The classification of data assets and research methods are all discussed reasonably.Domestic scholars' research on data assets assessment focuses on how to classify and classify data assets,the characteristics of data assets,and the construction of a basic assessment framework.Most of the research on valuation of big data assets is carried out on a specific,single issue.It can only approximate the relatively important quality indicators in the system.Even relatively systematic research can only be a general study.A model building point of view is presented and the relevant modeling steps are presented,but the complete system of the data asset value evaluation model cannot be systematically derived.As a new thing in the development of the Internet,data assets still need to be continuously studied,regulated,and improved.The evaluation of its asset value is a continuous process that needs continuous improvement.In the research process,this paper firstly analyzes the characteristics of data assets as a special intangible asset.Then according to the characteristics of data assets,the existing data assets assessment method was compared and analyzed.Finally,an analytic hierarchy process was used to build the assessment model.In the research process of AHP,it is possible to decompose complex decision-making problems,establish a hierarchy model,and then construct a judgment matrix based on the structural model,and obtain the weight coefficients corresponding to each index,and perform a total ranking of levels.Then elaborated on the indicators that affect the value of data assets in the data transaction process.Combining the opinions of past relevant research and data analysis experts,the judgment matrix of each index was determined.According to the judgment matrix,Matlab software is used to simplify the calculation procedure,obtain the corresponding weight and consistency test results,and quantitatively analyze the weight of each indicator.In the weights table,the data volume of the data is smaller in the overall assessment model.The data volume is not the most important factor in determining the value of the data;the data quality is higher than the data weight,and the inspection of the data quality is correct.The degree of satisfaction of the overall data to the data needs;the weight of data costs is greater than the data quality index,and the data cost is an effective measure of the input of the enterprise to the data research.The weight is higher than the data quality and data volume;the proportion of data mining is in the four indicators.The highest proportion of data mining,data mining is an effective measure of data applications,is an important feature of data assets.In addition,the standardized measurement of each indicator has also been elaborated,indicating the influencing factors of each indicator in the calculation process,and the specific calculation methods and range of values have been analyzed.This led to the final model of data asset assessment.Finally,the application of the model is studied in conjunction with specific cases.Taking the data assets of DT Map Technology as an example,detailed analysis of various indicators of data assets,and finally calculated the specific value of a certain amount of geographic information data held by the company.At the same time,there are some research deficiencies in the article.First of all,the data model lacks sufficient data to verify.At present,in the big data industry,the data transaction volume is small,the transaction is decentralized,there are many data transaction frameworks,and there are fewer public transactions.The data model construction method is difficult to analyze the algorithm directly in the transaction status.The tomography analysis method makes up for There are certain deficiencies,but there is still much room for improvement.In addition,due to the limited amount of reading and knowledge systems,it is impossible to completely cover the knowledge system needed for value evaluation of data assets.The further evaluation of the value of data,data quality,and data mining level requires more professional people to start from the Internet industry and provide more complete information.Knowledge support.Future big data assets will continue to play a role at different levels and in different industries,resulting in tremendous commercial value and social value.On the basis of traditional assessment methods,how to more reasonably assess pricing of data assets has become a new challenge for the asset valuation industry.