| In recent years, with the increase of flowers’trading volume, Kunming International Flower Auction Centre (KIFA) has accumulated a large number of data. However, the data accumulated is original and the trade information obtained is merely cross-section data, which cannot make us get market information dynamically, master the purchaser’s purchasing behavior and preference or even have an effective management of the supplier. Therefore, the key point currently is to have a further analysis of flower auction behavior and take effective measures to manage the purchasers and suppliers based on the existing database of KIFA.In response, opening the trading analysis, OLAP, data mining and data warehouse can help KIFA have a better understanding of consumption status and growing trend. On the basis of the above-mentioned needs, this paper has obtained relative indexes according to relevant theories, besides, it has conducted system developing and designing. What’s more, it has built an analysis system of flower trade in the light of a general method of information system design and development. Finally, this paper offers a brief introduction of the application in flower trading.The system gives a visualized analysis of the changes of some key indexes, such as supply quotient, buy quotient, deliquty, trading volume (sum involved), flow rate, complaints, commission and so on, which can assist KIFA to make relative operating decisions, improve office efficiency and precision of decision. |
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