| 課程大綱 Syllabus |
學生學習目標
Learning Objectives |
單元學習活動
Learning Activities |
學習成效評量
Evaluation |
備註
Notes |
序
No. | 單元主題
Unit topic |
內容綱要
Content summary |
| 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 |