Data Warehousing and Data Mining Course Plan
Subject Code : CS701 Semester : VII/IV CSE A
Subject : Data Warehousing and Data Mining
TEXT BOOKS
T1. Alex Berson and Stephen J. Smith, " Data Warehousing, Data Mining & OLAP", Tata McGraw – Hill Edition, Tenth Reprint 2007.
T2. Jiawei Han and Micheline Kamber, "Data Mining Concepts and Techniques", Second Edition, Elsevier, 2007.
| S. No | Topic | Book with Page no. | No of Hrs | Cumulative hrs | Teaching Aids |
| UNIT I DATA WAREHOUSING (10) | |||||
| | Introduction | Notes | 1 | 1 |
|
| Data warehousing Components | T1 (115-128) | 1 | 2 | NPTEL |
| | Building a Data warehouse | T1 (129 -150) | 2 | 4 |
|
| Mapping the Data Warehouse to a Multiprocessor Architecture | T1 (151-168) | 1 | 5 | OHP |
| DBMS Schemas for Decision Support | T1 (169 – 186) | 1 | 6 |
|
| Data Extraction, Cleanup, and Transformation Tools | T1 (187 -204) | 2 | 8 |
|
| | Metadata | T1 (205-220) | 2 | 10 | PPT |
| UNIT II BUSINESS ANALYSIS (8) | |||||
| Reporting and Query tools and Applications | T1 223 | 1 | 11 |
|
| | Tool Categories | T1 (223-226) | |||
| The Need for Applications | T1 (226-227) | 1 | 12 |
|
| | Cognos Impromptu | T1 (228-232) | 1 | 13 |
|
| | Online Analytical Processing (OLAP) | T1 247 | 1
| 14
| NPTEL |
| | OLAP Need | T1 247 | |||
| | Multidimensional Data Model | T1 (248-249) | 1 | 15 | PPT |
| | OLAP Guidelines | T1 (250-251) | 1 | 16 |
|
| | Multidimensional versus Multi relational OLAP | T1 251 | 1
| 17
| OHP |
| | Categories of Tools | T1 (251-255) | |||
| | OLAP Tools and the Internet | T1 (262-264) | 1 | 18 |
|
| UNIT III DATA MINING (8) | |||||
| Introduction | T2 (1-15) | 1 | 19 | NPTEL |
| Data – Types of Data | ||||
| | Data Mining Functionalities | T2 (21-27) | 1 | 20 |
|
| | Interestingness of Patterns | T2 (27-28) | |||
| | Classification of Data Mining Systems | T2 (29-30) | 1 | 21 | PPT |
| | Data Mining Task Primitives | T2 (31-33) | 1 | 22 |
|
| | Integration of a Data Mining System with a Data Warehouse | T2(34-35) | 1 | 23 |
|
| | Issues | T2(36-38) | 1 | 24 |
|
| | Data Preprocessing | T2(47-96) | 2 | 26 | OHP |
| UNIT IV ASSOCIATION RULE MINING AND CLASSIFICATION (11) | |||||
| Mining Frequent Patterns, Associations and Correlations | T2(227) | 1 | 27 | OHP |
| | Mining Methods | T2(234-249) | |||
| | Mining Various Kinds of Association Rules | T2(250-258) | 1 | 28 | NPTEL |
| | Correlation Analysis | T2(259-264) | 1 | 29 |
|
| Constraint Based Association Mining | T2(265-271) | 1 | 30 |
|
| | Classification and prediction - Basic Concepts | T2(285) | 1 | 31 |
|
| | Decision Tree Induction | T2(291-301) | 1 | 32 | OHP |
| | Bayesian Classification | T2(310-317) | 1 | 33 | PPT |
| | Rule Based Classification | T2(318-326) | 1 | 34 |
|
| | Classification by Back propagation | T2(327-336) | 1 | 35 |
|
| | Support Vector Machines | T2(337-343) | |||
| | Associative Classification | T2(344-346) | 1 | 36 |
|
| | Lazy Learners | T2(347-350) | |||
| | Other Classification Methods | T2 (351-353) | |||
| | Prediction | T2 (354-358) | 1 | 37 |
|
| UNIT V CLUSTERING AND APPLICATIONS AND TRENDS IN DATA MINING (8) | |||||
| Cluster Analysis | T2 (383 - 385) | 1 | 38 |
|
| | Types of Data | T2 (386 - 397) | |||
| | Categorization of Major Clustering Methods | T2 (398 - 400) | 1 | 39 |
|
| | K means | T2 (401) | |||
| | Partitioning Methods | T2 (401 - 407) | |||
| | Hierarchical Methods | T2 (408 - 417) | 1 | 40 | PPT |
| Density-Based Methods | T2 (418 - 423) | |||
| | Grid Based Methods | T2 (424 - 428) | 1 | 41 |
|
| | Model-Based Clustering Methods | T2 (429 - 433) | 1 | 42 |
|
| | Clustering High Dimensional Data | T2 (434 - 443) | |||
| | Constraint – Based Cluster Analysis | T2 (444 - 450) | 1 | 43 |
|
| | Outlier Analysis | T2 (451 - 459) | 1 | 44 |
|
| | Data Mining Applications and Overview Overall Review | T2 (649 - 659) | 1 | 45 | OHP |
Total = 45 Hours
Further Reading and References:
Related Websites
| S. No | Website Name |
| 1 | |
| 2 | |
| 3 | |
| 4 |
Advanced Topics
| S. No | Advanced Topics | Related Topic in Syllabus |
| 1 | Machine Learning | UNIT – IV (Classification and Prediction) |
| 2 | Web Data Mining | UNIT – V (Data Mining Applications) |
Related Journals
| S. No | Journal Name | Website Name |
| 1 | ||
| 2 | Data Mining and Knowledge Discovery: An International Journal | |
| 3 | IEEE Transactions on Pattern Analysis and Machine Intelligence |
Related NPTEL Course Materials
| S. No | Course Name | Co-Ordinator & Institute | Website Name |
| 1 | Data warehousing Components -Video | Learningdom online Training | |
| 2 | Introduction to Data Mining- Video | Dr. S. Srinath, IIT Bangalore | |
| 3 | Mining Various Kinds of Association Rules Video | Dr. S. Srinath, IIT Bangalore |
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