| In recent years,due to the rapid development of related fields such as Internet,cloud computing and data as a service,personal data,enterprise data and government data,the amount of data has exploded.As the great value of data drives data transactions,data marts have been established at home and abroad.Data products,as a new product form,are obtained by data integration of one or more data sources.In a broad sense,they refer to products that can give play to data value and assist users to make better decisions or direct actions.Similar to information products,data product development needs the participation of consumers to ensure the embodiment of value.At the same time,there are similarities between data products and traditional physical products in the basic production process.Customized data products refer to providing data products or data services required by data consumers according to their personalized characteristics,and assisting data consumers to make decisions by using data products or data services.Data product development and information products need the participation of consumers to ensure the embodiment of value.How can data products be customized.How do you make decisions about data source selection during data product customization.How can data platforms be priced for customized data products.Based on previous studies,this paper considers the above related issues,and the main research content and innovation work mainly include:(1)This paper introduces the basic concept and related applications of data products,and describes the characteristics of data products.The design and pricing of traditional products and information products,data products,data integration and data quality are reviewed.(2)Data product customization design based on multi-source data integration.According to the historical data of consumers,k-means clustering analysis is conducted for consumers,and the importance degree of various consumer demand characteristics is calculated.This paper is a data product customization design based on multi-source data integration.By referring to the design steps of traditional products based on QFD theory and taking data sources as technical requirements,the design steps of data products based on QFD theory are proposed.According to the research of relevant data quality and data integration,a customized data product quality model of multi-source data integration is proposed.(3)Data product customization design and pricing strategy based on multi-source data integration.Data products in the design process,the different data sources with different quality and cost,consider the cost of production data and the influence of consumer choice,data platform and data consumers,this paper puts forward the multiple data product design and pricing decision of bi-level programming model,and uses genetic algorithm and particle swarm optimization algorithm to solve the data of the product design and pricing decisions;(4)Based on the actual situation,this paper takes A data platform as an example to obtain the needs of data consumers and establish A double-layer programming model according to the relevant data provided by A data platform.Considering the revenue maximization of the data platform and the self-selection decision of the data consumers.determine the data source selection decision of the data product and the pricing decision of the data product.This paper presents the steps of data product customization design based on multi-source data integration,give full consideration to consumer demand,data platform is given for the selection of data source in the process of product design and product pricing model,data for the data provide a basis for data production and trading platform,has very important theory and practice. |
