Research On Data Quality Management Of New Retail Industry

Jack ma,President of Alibaba,put forward the new term "new retail"for the first time at the 2016 Alibaba Apsara conference.That is,no matter online or offline,no matter which sales channel,can do " Consumers can be identified,reached and operated." However,the situation of offline customer flow is an important information in the operation process,and sufficient and stable customer flow is the premise for the mall to achieve good profits.With the rapid development and popularization of computer technology,all business links of an enterprise have basically realized digitalization and accumulated a large amount of operation history data.However,the current data is relatively single,so it is difficult to analyze the overall customer preference,so it is difficult to make decisions for the refined operation of a business.Massive user behavior data is a necessary condition for the implementation of offline operating solutions,while the accurate operation plan depends on high-quality data,which will not only affect the decision-making results,but also cause economic losses,so it is urgent to improve the data quality of offline retail industry.Big data quality is the basis of all data analysis,mining and decision support.The characteristics of retail data and users' expectation and perception of data quality bring new challenges to the research of data quality.Although some research results have been achieved in the field of big data quality management at home and abroad,offline retail data has the characteristics of long data link,affected by offline hardware environment,network environment and other factors,and the existing methods are difficult to apply to the quality management of offline retail big data.Therefore,strengthening the quality management of offline retail big data is not only the need for AI and big data technology to penetrate the offline retail industry,but also very urgent.This paper studies the offline retail data quality management by combining theory with practice and management knowledge,especially the knowledge related to total quality management.First of all,by introducing the main idea of total quality management,this paper analyzes the main problems of data quality management in offline retail industry,and applies the theory of total quality management to retail big data quality management.Then,according to the actual situation,the relevant rules of data quality inspection are designed and implemented.Finally,taking company a as an example,the data quality management adopted by company a is analyzed and studied,so as to verify the effectiveness of TQM theory in retail big data quality management.I hope the research results of this paper can bring some reference significance to the quality management of offline retail big data.