Design And Implement Of Retail Report System Based On Data Granularity Precomputation

Report system has always been the basic business requirements of enterprises,the basic measures and ways of enterprise management,and the basis of the implementation of business intelligence strategy.With the expansion of retail enterprise and the rapid accumulation of historical data,in the field of business intelligence,how to make multidimensional statistical analysis and display of massive retail data has become an urgent problem to be solved in the report system.In this context,a design and implementation of a retail report system based on data granularity precomputation is proposed.Firstly,the present situation of report management in retail enterprise is introduced in this paper,at the same time the research contents of report system construction based on big data at home and abroad,the theory of data warehouse and the related big data processing technology are analysed,and the idea of predicting and calculating the exchange of space for time is determined.Then,according to the business requirement analysis and functional requirement analysis,the goal of the system is defined,and based on the analysis the data processing scheme is designed.Around the multi-dimensional data preprocessing module,Apache Kylin analysis engine is used to construct data cube and stored procedure is used to realize materialized view,thus completing the prediction and storage of massive retail data,and improving the efficiency of multi-dimensional data analysis and query in report system.Finally,the SSM(Spring SpringMVC MyBatis)web framework is used to build the report management platform.In the whole design process of the project,the author is mainly responsible for the design of data warehouse,the design of prediction module and the design and development of report platform.In terms of experimental verification,the correctness of the design of predictive tasks is verified through task scheduling platform firstly.Then,the performance of the preprocessing scheme and the overall query performance of the system are verified,which verifies the improvement of the query performance of the system based on the pre-computing scheme.Finally,the OLAP analysis method is used to analyze and query the data of the system,and the functional requirements of the system are verified.