Research On Brand Knitwear Design Optimization In Era Of Big Data

Due to the advent of the era of big data, human society has entered the digital age. Data information has undergone a substantial increase, penetrated into all aspects of social life, and promoted great reforms of human life styles and social productivity.As a result, consumer demands in the market have changed. Driven by constantly development and progress of high and new technologies such as information technology,network technology and social media technology, knitting fashion has changed rapidlyand diverse fashion information has been shown constantly. On the one hand, brand knitwear companies should adjust their strategies based on above changes, realize dataanalyses and sharing, widely apply data in design and development of brand products,and hold an active attitude to deal with rapid changes in fashion replacement and consumer demands. On the other hand, competitions among brand knitwear companies have become increasingly intense. Product homogeneity has become more and more serious. Brand knitwear companies need to make adjustments of their product design anddevelopment links, in order to keep a foothold in the fierce market competition.On the basis of analyses made above, the theory of big data and brand knitweardesign theory, principles and methods of disciplines such as the brand clothing design,computer science and statistics and so on are used to make big data analyses and utilization, so as to propose the data warehouse-based decision support theory for brandknitwear design.First of all, design information is extracted from relevant information about brandknitwear design obtained from various sources and collated, thus building a data warehouse for brand knitwear design information.Secondly, the multi-dimensional data mining principles for data cubes, and tools such as multidimensional data cube, OLAP star data mining model and multi-dimensional tables are used to realize data mining of brand knitwear design information, in hope of obtaining information about design elements.Lastly, the decision support method for brand knitwear design based on data warehouse is proposed. Moreover, a preliminary simulation experiment is made in practice.Human-computer interaction tools are used for preliminary demonstration and analysesof the experimental process and results, to validate the feasibility of this method.In this paper, propose the data warehouse-based decision support theory for brandknitwear design. This theory can make the brand knitwear design accord with constantly-changed market consumer demands and fashion trends in a more scientific, accurate and effective way, help knitwear design companies to avoid blindness caused by subjective judgment made by designers solely replying on their personal experience, reduce the possibility of the brand product homogeneity, lower the risk of blindly releasing products into markets, effectively guide development and enhance the core competitiveness of enterprises, in the process to develop products.