BI 系統最主要的功能是整理龐大資料，轉化為有用訊後產生報表給 主管做決策的參考，因此資料新鮮度成為非常重要議題；越代表 主管做決策的參考，因此資料新鮮度成為非常重要議題；越代表 主管做決策的參考，因此資料新鮮度成為非常重要議題；越代表 主管做決策的參考，因此資料新鮮度成為非常重要議題；越代表 主管做決策的參考，因此資料新鮮度成為非常重要議題；越代表 著主管所獲取的資料越即時 (real time)，主管可以藉著這些資料做出更為準確的決 ，主管可以藉著這些資料做出更為準確的決 策。但是處理資料的過 程必須經ETL ETL的步驟， ETL ETL的架構複雜且處理時間久， 資料往喪失其新鮮度。許多企業為了解決此問題，開發以即時 (real time)為目的資料儲存體(cube)工具，但是多樣化的選擇卻造成了決策上困難。因此本研究的主要目為建立資料儲存體 (cube)模型，幫助使用者在不同新 鮮度及限制下的資料儲存體 (cube)中做選擇，避免浪費時間在不合需求的工具執 行The most important purpose of BI system is to store integrated data for helping mangers making decisions with timely reports, which need to be generated in a limited time interval and containing fresh data.Data cleansing and integration is very time consuming operations, which may take hours to be completed in many organizations. With the long processing time, some organizations opt to execute the operations in batch, which may be executed in less business hours to speed up system performance in trading of freshness. On the other hand, some reports such as inventory level summary, many need most current data which need to be load into BI systems in the real time. Therefore, users have to make decisions if the data cleansing and integration operations need to be processed in real time or in batch for every reports. This research proposes a methodology to suggest the decision based on the freshness requirement and waiting time users are willing to wait for reports.
