課程名稱 |
(中文) 資料倉儲 (英文) Data Warehousing |
開課單位 | 資訊經營研究所 | ||
課程代碼 | N5350A | ||||
授課教師 | 陳明賢 | ||||
學分數 | 3.0 | 必/選修 | 選修 | 開課年級 | 研究所 |
先修科目或先備能力:資料庫系統及企業流程相關知識 | |||||
課程概述與目標:The data warehouse industry has reached full maturity and acceptance across the business world. This course helps students get about the business of building and managing a data warehouse that is a platform for business intelligence applications. | |||||
教科書 | 1, Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling," 3nd Ed., Wiley, 2013, ISBN: 9781118530801 | ||||
參考教材 | 1, Ralph Kimball, Margy Ross, "The Kimball Group reader : relentlessly practical tools for data warehousing and business intelligence," Wiley, 2015 | ||||
圖書館電子書 | http://www.sciencedirect.com/science/book/9780123743190 http://www.sciencedirect.com/science/book/9781558606845 http://link.springer.com/book/10.1007%2F978-3-540-74405-4 http://link.springer.com/book/10.1007%2F978-1-4302-0528-9 http://www.sciencedirect.com/science/book/9780123737267 https://link.springer.com/book/10.1007%2F978-1-4842-0082-7 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119228912 |
課程大綱 | 學生學習目標 | 單元學習活動 | 學習成效評量 | 備註 | ||
週 | 單元主題 | 內容綱要 | ||||
1 | Evolution of Decision Support Systems | 1. The Evolution 2. Problems with the naturally evolving architecture 3. The architected environment 4. Who is the user 5. The development life cycle |
1能具體描述DSS沿革 |
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2節 |
2 | The data warehouse environment | 1. The structure of the data warehouse 2. Subject orientation 3. Day 1-day n phenomenon 4. Granularity 5. Cost justification |
1能具體描述資料倉儲特徵 2能區別資料庫與資料倉儲之異同 |
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2節 |
3 | Introducing the Kimball Lifecycle | 1. Lifecycle History Lesson 2. Lifecycle Milestones 3. Using the Lifecycle Roadmap 4. Lifecycle Navigation Aids 5. Lifecycle Vocabulary Primer |
1能按Kimball Lifecycle進行小型資料倉儲專案規畫 |
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2節 |
4 | Dimensional modeling primer | 1. Dimensional modeling vocabulary 2. Dimensional modeling myths |
1能描述何謂維度為模 2區別維度模型與正規化模型之差異 |
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1節 |
5 | Retail Sales | 1. Four-step demensional design process 2. Declar the grain 3. Choose the demensions 4. Identify the facts |
1能以維度計設四步驟進行維設建模 2能辨別不同的資料顆粒度 |
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3節 |
6 | Inventory | 1. Periodic snapshot 2. Transaction snapshot 3. Accumulation snapshot 4. Data warehouse bus matrix 5. Conformed dimensions and facts |
1能區別三種類型的資料顆粒度 2在維度設計時能恰當選顆粒度 |
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3節 |
7 | Procurement | 1. Multiple- VS Single- transaction fact tables 2. Slowly changing dimensions 3. More rapidly changing demensions |
1能判斷何時該採單一事實表或多重事實表 2具體描述三種不同類型的漸變維度 3區別漸變維度與快變維度 |
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3節 |
8 | Order Management | 1. Fact normalization 2. Dimension role-playing 3. Degenerate dimension 4. Junk dimensions |
1能運用維度角色扮演、退化維度、雜項維度等技巧於維度計設 |
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2節 |
9 | Other Dimensional modeling issues | 1. Large changing dimensions 2. Consolidated fact tables 3. Time-stamped transaction tracking in a dimension 4. outrigger dimension 5. Household dimension 6. Multivalued dimensions 7. Surrogate keys |
1運用本單元所授的技巧於維度設計 |
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3節 |
10 | Term project veview (1) | Review the design of dimensional model | 1運用於本課所習的知識,設計一小型資料倉儲 2確認學期專題的維度模型之正確性 |
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3節 |
11 | Overall introducing Extract, Transformation, and Load | 1. Round Up the Requirements 2. Extracting Data 3. Cleaning and Conforming Data 4. Delivering Data for Presentation 5. Managing the ETL Environment |
1能整體概述ETL |
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3節 |
12 | Introducing Data Integration | 1. Data Integration Concepts 2. BigData Overview 3. Velocity Methodology of Data Integration 4. Introducing Informatica PowerCenter |
1具體描述業界常用的ETL產品 |
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3節 |
13 | Designing Data Integration Process with ETL Tools (1) | 1. Extract, Transform, Load 2. PowerCenter Components and User Interface 3. Config Lab environment 4. Processing Operational Data Store |
1ETL工具基本功能操作 2運用ETL工具處理ODS |
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3節 |
14 | Designing Data Integration Process with ETL Tools (2) | 1. Processing Operational Data Store (cont.) 2. Processing Dimension Tables |
1運用ETL工具處理維度表 |
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3節 |
15 | Designing Data Integration Process with ETL Tools (3) | 1. Processing Dimension Tables (cont.) 2. Processing Fact Tables |
1運用ETL工具處理事實表 |
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3節 |
16 | Introduce Profiling , Analyze and Data Quality | 1. Introducing Data Profiling 2. Introducing Data Analyze 3. Introducing Data Quality |
能判斷資料來源的資料品質 |
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3節 |
17 | Term project review(2) | Review the design of ETL process | 1運用於本課所習的知識,設計一小型資料倉儲 2確認學期專題的ETL程序之正確性 |
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3節 |
18 | Term project presnt, Mid Exam, Final Exam | Term project present | 1展示學期專題成果 |
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3節 3節 3節 |
教學要點概述: |
核心能力 | 期末考 | 期中考 | 其他評量 | 專題 | 平時考 | 作業 | ||
核心能力一 | 學術研究能力 | 3/10 | 3 | 3 | 3 | 3 | 3 | 3 |
核心能力二 | 技術發展能力 | 5/10 | 5 | 5 | 5 | 5 | 5 | 5 |
核心能力三 | 服務管理能力 | 2/10 | 2 | 2 | 2 | 2 | 2 | 2 |