The Research And Realization Of Association Rules Teachniques Facing The ERP System

Data Mining,also named as KDD(Knowledge Discovery in Database),is a decision support method in which we can pick up many connotative,unkn-own,potential and useful knowledge or information mode from database or data warehouse .The knowledge that is discovered by means of Data Minning can reflect a certain facts and guide practice. Association rules can discover the rules among products from database or DW , These rules can find the mode of customer's buying behavior.For example,buying one product affects the behaviors of buying another product.Those association Rules are used to prospect products saling, organize manufacture production,products stock. If DM techniques,especially to association Rules, are used in manufacturing,most of enterprises can benefit a lot.Though Guizhou 3537 Shoes-Making Factory ERP System can resolve many problems on production and sales effectively,it isn't perfect enough in analysis,forecast and decision-making.After analyzing 3537 Shoes-Making Factory ERP System,we try to use Assocition Rules to improve it: We built a data warehouse that is used in consignment analysis. Assocition Rules are used to find out the selling-relationship among varied products.Sales department can take measures to gain best marketing result. In the end of this thesis,conclusions are given.There are two distinguishing features of this thesis: First, it includes some new contents.Because both the data mining and ERP are new technologies which develop in recent years and their application and research in our country just begin. I have to read a lot of foreign articles during writing the thesis. Second, it sees the problem from a new viewpoint.ERP is a course of enterprise's managing resouses,combining modern management and computer technology. it is very large system and its content is lot.I do not do the research from management and other technology being used in ERP but do the research from its core technology of sell management to widen the field of the using of Assocition Rules.