本課程旨在研讀決策支援系統之基本原理與架構，幫助學生運用資訊來協助最佳決策的制定。內容除理論介紹外，亦將分組探討DSS應用。
課程內涵(Course Contents)共分成三大部分：
1. 決策支援系統與企業智慧：現代決策支持、決策支持概念、識別決策支持的類型、使用大數據進行決策支持、商業智能和數據驅動的DSS、預測分析和模型驅動的決策支持、決策支持的取捨、分析確認決策支持機會。
2. 大數據分析技術：Large-Scale File Systems and Map-Reduce / Finding Similar Items、Frequent Itemsets / Link Analysis / Clustering。
3. 應用探討(臨床決策支援系統)：臨床指引(Clinical Guideline)/ 臨床決策知識表達法 / 醫療保健分析(Healthcare Analytics)。This course aims to study the basic principles and structure of the decision support system and help students use information to assist in the formulation of the best decisions. In addition to theoretical introduction, the content will also be explored in the DSS application in a sub-group.
Course Contents are divided into three parts:
1. Decision support system and enterprise wisdom: modern decision support, decision support concept, identification of type of decision support, use of large data for decision support, DSS for business intelligence and data drive, prediction analysis and model drive decision support, decision support for decision support, decision support for decision support, analysis and confirmation decision support opportunities.
2. Large-Scale File Systems and Map-Reduce / Finding Similar Items, Frequent Itemsets / Link Analysis / Clustering.
3. Application Exploration (Clinical Guidelines)/Clinical Guidelines Knowledge Expression Methods/Healthcare Analytics.
Power, Daniel J.; Heavin, Ciara., “Decision Support, Analytics, and Business Intelligence (3rd ed.)”, Business Expert Press., LLC, 2017.
Power, Daniel J.; Heavin, Ciara., “Decision Support, Analytics, and Business Intelligence (3rd ed.)”, Business Expert Press., LLC, 2017.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 家庭作業家庭作業 Homework |
60 | 實例演算並作分析討論，本學期計4~6次。 |
| 期末報告(書報討論)期末報告(書報討論) Final report (book discussion) |
40 | 每組口頭報告一篇。 |
