141 653 data warehousing and data mining
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141-653 Data Warehousing and Data Mining. ดร. วิภาดา เวทย์ประสิทธิ์ ภาควิชาวิทยาการคอมพิวเตอร์ มหาวิทยาลัยสงขลานครินทร์ ห้อง CS 320 E-mail : [email protected] Website : http://staff.cs.psu.ac.th/wiphada. วัตถุประสงค์.

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141-653 Data Warehousing and Data Mining

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141 653 data warehousing and data mining

141-653 Data Warehousing and Data Mining

.

CS 320E-mail : [email protected]

Website : http://staff.cs.psu.ac.th/wiphada


141 653 data warehousing and data mining

1.

2.

3.

Chapter 1


141 653 data warehousing and data mining

35%

40% Assignment 15%

10%

13.00 16.00 S104

Chapter 1


141 653 data warehousing and data mining

Chapter 1 : Introduction

Chapter 2 : Data Warehouse

Chapter 3 : Data Mining

Chapter 4 : Basic Data Mining Techniques

Chapter 5: Decision Tree

Chapter 6: Association Rules

Chapter 7: The K- Means Algorithm

Chapter 8: Neural Networks

Chapter 9 : Statistical Techniques

Chapter 10 : Rule-Based Systems

Chapter 1


141 653 data warehousing and data mining

1. Data Mining A tutorial-Based Primer, Richard J. Roiger and Michael W. Geatz,

Pearson Education Inc., 2003.

2. Mining Very Large Databases with Parallel Processing, Alex A. Freitas

and Simon H. Lavington, Kluwer Academic Publishers, 1998.

3. (Data Warehouse), ,

, 2546

4. (Decision Support

Systems and Expert Systems), ,

, 2546

Chapter 1


Chapter 1

Chapter 1

Introduction


Content

Content

  • Data Warehouse ()

  • Data Warehousing ()

  • Data Mining ()

Chapter 1


141 653 data warehousing and data mining

  • 1. H/W S/W

  • 2. Data Redundancy

  • 3. Data Inconsistency

  • 4. Coding System (Multiple Standard)

  • (Silo-based System)

Chapter 1


141 653 data warehousing and data mining

  • Business Integration

  • 2

  • 1. Partial Business Integration

    • Point to Point Business Integration

    • Middleware Business Integration

  • 2. Overall Business Integration

Chapter 1


141 653 data warehousing and data mining

  • 1. Partial Business Integration

    • Point to Point Business Integration

      • 2

      • Spaghetti Phenomenon

    • Middleware Business Integration

      • H/W S/W

Chapter 1


Point to point business integration

Point to Point Business Integration

Chapter 1


141 653 data warehousing and data mining

  • 2. Overall Business Integration

    • Unified Standard

    • Maximize data consistency

    • Minimize data redundancy

Chapter 1


Data warehouse

Data Warehouse ()

  • ....

  • ....

  • (Organization Customized System)

Chapter 1


141 653 data warehousing and data mining

  • 1. Subject-Oriented

  • 2. Integrated

  • 3. Time-Variant

  • 4. Non-Volatile

Chapter 1


141 653 data warehousing and data mining

  • 1. Subject-Oriented

    • ........

  • 2. Integrated

Chapter 1


141 653 data warehousing and data mining

  • 3. Time-Variant

    • 5-10

  • 4. Non-Volatile

    • ....... Normalize (Data based)

Chapter 1


141 653 data warehousing and data mining

  • 1.

  • 2.

  • 3.

Chapter 1


141 653 data warehousing and data mining

  • 1.

  • 2.

  • 3.

  • 4.

Chapter 1


Data warehousing

Data Warehousing ()

Chapter 1


141 653 data warehousing and data mining

  • 1. Data Acquisition System

  • 2. Data Staging Area

  • 3. Data Warehouse Database/Data Store

  • 4. Data Provisioning Area /Data Mart

  • 5. End User Terminal

  • 6. Metadata Repository

Chapter 1


141 653 data warehousing and data mining

Chapter 1


141 653 data warehousing and data mining

  • 1. Data Acquisition System

  • 2. Data Staging Area

    • Data Cleansing

    • Filtering

  • 3. Data Warehouse Database/Data Store

    • Data Model

Chapter 1


141 653 data warehousing and data mining

  • 4. Data Provisioning Area / Data Mart

  • 5. End User Terminal

    • Simple Report Tool

    • Multi Dimensional Tools

    • Data Mining Tools

  • 6. Metadata Repository

Chapter 1


141 653 data warehousing and data mining

  • 1. Query and Report Generator

  • 2. Multidimensional Data Analysis

  • 3. Online Analysis Processing (OLAP)

  • 4. Data Mining Tools

Chapter 1


141 653 data warehousing and data mining

Chapter 1


141 653 data warehousing and data mining

Chapter 1


Online analysis processing olap

Online Analysis Processing (OLAP)

  • (Multidimensional Data Analysis)

  • OLAP

    • 1. Roll up / Consolidation

      • .....

    • 2. Drill Down

      • .....

    • 3. Slice

    • 4. Dice

Chapter 1


Data mining

Data Mining ()

  • Application

  • (Knowledge Discovery)

  • (Rule)

Chapter 1


141 653 data warehousing and data mining

  • 1. Classification

  • 2. Clustering

  • 3. Association

  • 4. Visualization

Chapter 1


141 653 data warehousing and data mining

p.85

  • 1. Classification :

    • (Predictive Model) ......Supervised Learning

    • 2

      • Tree Induction

      • Neural Network

  • 2. Clustering : .......Unsupervised Learning

  • 3. Association :

  • 4. Visualization :

Chapter 1


141 653 data warehousing and data mining

  • 1.

  • 2.

  • 3.

  • 4.

Chapter 1


141 653 data warehousing and data mining

  • 1.

  • 2.

  • 3.

  • 4.

  • 5.

  • 6.

  • 7. H/W S/W

  • 8.

  • 9.

Chapter 1


141 653 data warehousing and data mining

  • 1.

  • 2. Client/Server

  • 3.

  • 4.

  • 5.

Chapter 1


Homework 1

Homework1

  • 1. 2

    • Data Warehouse ()

    • Data Mining ()

  • 2. Data Mining Tool

    (next week in class)

    • Hard Copy

    • File

    • Presentation 2 min (no slide)

Chapter 1


141 653 data warehousing and data mining

The road to success is always

under construction

Jim Miller


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