本課程以統計角度，介紹大數據與現行產業間之關聯外，並進一步介紹資料採礦工具與方法，配合統計軟體SAS Enterprise Guide 和 SAS Enterprise Miner的使用，訓練學生從大量和複雜的資料中發掘重要的決策資訊，培養同學研究與解決問題的能力。
This course introduces the methods in data mining through the statistical point of view. Students will learn the ability to analyze massive and complicated data and will be able to turn the raw data into valuable information using SAS Enterprise Guide & SAS Enterprise Miner.This course not only introduces the relationship between big data and current industries from a statistical perspective, but also further introduces data mining tools and methods. It uses the statistical software SAS Enterprise Guide and SAS Enterprise Miner to train students to discover important information from large and complex data. decision-making information and cultivate students’ research and problem-solving abilities.
This course introduces the methods in data mining through the statistical point of view. Students will learn the ability to analyze massive and complicated data and will be able to turn the raw data into valuable information using SAS Enterprise Guide & SAS Enterprise Miner.
智聯網時代的來臨，改變資料蒐集與儲存的技術，加速資料的取得與累積，大幅改變資料的應用方式。「大數據」(Big Data)或稱「巨量資料」的分析與資料挖礦，4V即指用以取決巨量資料的整備度：巨量（Volume）、高速（Velocity）、多樣（Variety）、價值（Value），完整無遺地掌握巨量資料4V，就能從混沌的巨量資料邁向進階的巨量資料分析。大數據分析的基礎與應用為統計與資料分析方法，進進一步利用統計資料挖礦，發掘先前未知且潛在有用的資訊樣型，進而轉化為有價值的資訊或知識，此外在巨量資料的環境下，許多的應用情境需要在未儲存資料前就要採取行動，以符合現在環境需求。課程內容含括資料預處理、資料挖礦入門、資料挖礦技術與軟體實作，依序介紹SAS Enterprise Guide (SAS/EG)和SAS Enterprise Miner(SAS/EM)，同時希望完成課程時，能協助學生：(1)通過SAS Enterprise Guide 檢測，具足資料整理、合併檔案、欄位新增、資料彙總以及報表製作這五大面向，(2) 製作專業化巨量資料視覺分析簡報，(3)精熟資料挖礦技術，如關聯法則、決策樹分析、集群分析、迴歸分析、和模型選擇與整合。除依序介紹資料挖礦的工具與方法外，著重利用專案及軟體操作訓練同學研究與解決問題的能力。
The advent of the Internet of Intelligence era has changed the technology of data collection and storage, accelerated the acquisition and accumulation of data, and significantly changed the way data is used. "Big Data" or "massive data" analysis and data mining, 4V refers to the degree of readiness used to determine huge amounts of data: Volume, Velocity, Variety , value (Value), if you completely master the massive data 4V, you can move from chaotic massive data to advanced massive data analysis. The basis and application of big data analysis are statistics and data analysis methods, and further use statistical data mining to discover previously unknown and potentially useful information patterns, and then transform them into valuable information or knowledge. In addition, in the environment of huge amounts of data Under the current circumstances, many application scenarios require taking action before storing data to meet the needs of the current environment. The course content includes data preprocessing, introduction to data mining, data mining technology and software implementation. It introduces SAS Enterprise Guide (SAS/EG) and SAS Enterprise Miner (SAS/EM) in sequence. At the same time, I hope to be able to Assist students: (1) Pass the SAS Enterprise Guide test and meet the five major aspects of data sorting, merging files, adding fields, data summary and report production, (2) Produce professional visual analysis briefings on huge amounts of data, and (3) be proficient in data mining techniques, such as correlation rules, decision tree analysis, cluster analysis, regression analysis, and model selection and integration. In addition to introducing the tools and methods of data mining in sequence, it also focuses on using projects and software operations to train students' research and problem-solving abilities.
1. Tan, Steinbach and Kumar, Introduction to Data Mining, Addison Wesley, 2006. (歐亞)
2. 曾淑峰、林志弘、翁玉麟（2012年9月），資料採礦應用—以SAS Enterprise Miner為工具，梅霖文化事業有限公司 (ISBN: 978-986-6511-60-8)
3. Slaughter, S.J. and Delwiche, L.D., 蔡宏明、蔡秉諺譯（2011年11月），SAS Enterprise Guide實用工具書，梅霖文化事業有限公司 (ISBN: 978-986-6511-58-5)
1. Tan, Steinbach and Kumar, Introduction to Data Mining, Addison Wesley, 2006. (Eurasia)
2. Zeng Shufeng, Lin Zhihong, and Weng Yulin (September 2012), Data Mining Application—using SAS Enterprise Miner as a tool, Meilin Cultural Industry Co., Ltd. (ISBN: 978-986-6511-60-8)
3. Slaughter, S.J. and Delwiche, L.D., translated by Cai Hongming and Cai Bingyan (November 2011), SAS Enterprise Guide, Meilin Cultural Enterprise Co., Ltd. (ISBN: 978-986-6511-58-5)
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