Research On Analysis Methord Of Business Data Based On Port OLAP System

With the globalization of the world economy and the development of modern logistics,port affects a lot on the surrounding areas and hinterland,and gradually becomes a modern integrated logistics center.However,due to the growing competition between ports,the requirement of the data content and quality made by companies and customers are much stricter.The rapid growth of business volume makes it difficult for port enterprises to analyze and discover the useful rules in data,and decision support information can not be obtained accurately and timely.Therefore,it is necessary to use effective analytical tools and mining methods to extract valuable relationships from complex decentralized data sources to provide scientific and theoretical support for the scientific decision-making of port enterprises.This thesis builds the OLAP analysis platform of coal port production data,the main work is as follows.Firstly,a prediction algorithm of port coal business based on time series exponential smoothing model is proposed.The algorithm preprocesses the data using the time series exponential smoothing prediction method,using the actual number and forecast value of the previous period,we use the method of index weighting for forecast,after the ETL process to further clean the data,the conversion is loaded into the data warehouse,making the data suitable for OLAP analysis technology application requirements,and to achieve the port coal throughput forecast.Secondly,an algorithm for mining association rules of port coal service equipment maintenance is proposed.The algorithm performs frequent pattern mining for different dimensions of the coal service equipment maintenance business,and accurately forecasts the time of failure of the equipment.By mining the relationship between the data fields in the port production business,we can get the strong relation behind the data and provide the theoretical service for the daily decision of the port.Finally,the OLAP analysis method is applied to all aspects of the coal production business theme to deal with the complex data in the port coal data warehouse.Based on the data preprocessing technology and association rule mining method,the port OLAP system is designed and the production data can be analyzed intelligently.In this thesis,the algorithm is written in the Java,the experimental results show the effectiveness of the algorithm in the port business data analysis.