Course goals

A major challenge in this course is to balance the need between technical skill and managerial insight so that students can gain an overview of the whole subject area while at the same time being able to obtain some hand-on experience.  We highlight the following two technical skills that are most relevant to the course.

Some Basic Knowledge of a Database Management Systems (DBMS) :

Data Analysis Skills :

Textbooks:

Chris Todman, Designing A Data Warehouse: Supporting Customer Relationship Management, 1/e, Prentice Hall, 2001, ISBN 0-13-089712-4 
Berry, M.J.A. and Linoff, G., Data Mining Techniques: for Marketing, Sales, and Customer Support, John Wiley & Sons, 1997, ISBN 0-471-17980-9 

There are many books published recently in this area. 

1.    Intelligent Enterprise ( http://www.intelligententerprise.com/), Netlibrary, Business Week, cnnfn.com, Earthweb.com, etc. 
2.    Turban and Aronson, Decision Support Systems and Intelligent Systems, 6/e, Prentice Hall, 2001 
3.    Amrit Tiwana, Essential Guide to Knowledge Management , The: E-Business and CRM Applications, 1/e,  Prentice Hall, 2001 
 

Course Outline: 

Weekly topics: 

Week 1: Review of DBMS and Overview of Business Intelligence (T Chapter 1 & BL Chapter 1) 
    Key Contents: Relational Database, Entity-Relationship model, Normalization, MS Access, DB2, CRM 
Week 2: Data Mining Overview (BL Chapters 2-7) and Data Warehousing Overview (T Chapters 2-4) 
    Key Contents:  Values of data mining, Transactional Database and Data Warehouse, Star vs. snow-flake schemas,  Object-oriented design 
Week 3: Analytical Models  Part I (BL Chapter 8-10) and Conceptual Logical model and Implementation (T Chapters 5-7) 
    Key Contents: Market Basket model, Memory-Based Reasoning, and Cluster Analysis, Introduction to TPC database and project 
Week 4: Four analytical Models Part II (BL Chapter 11-14)
    Key Contents: Link Analysis, Decision Tree model , Artificial Neural Networks, and Genetic Algorithms 
Week 5: Data mining and Corporate Data warehousing  (BL Chapter 15, 17, 18  T: Chapters 9-10   ) 
    Key contents: Planning, Implementing, and Controlling of Data Warehousing/ Data Mining Projects 
Week 6: OLAP (BL Chapter 16) and TPC Project Review 
Week 7: Implementation and Discussion of the Project. 
Week 8: Final Examination 
 

Grading Policy

1.    Assignments (20%): several prototype model constructions are assigned as homework 
2.    Participation (20%): Students are expected to participate in class discussions.  In addition, each student will be assigned a topic and be responsible for finding supplementary information for the subject. 
3.    Exams (30%): There will be a final exam. 
4.    Projects (30%): A project to design and implement an intelligent system will be assigned. 
 

Project

Option I: a more technical option

The project requires student to plan, implement, and control the project of building an intelligent model based on a given transactional database (TPC-H) obtained from the Transaction Processing Performance Council ( http://www.tpc.org ).  The database is generated by C programs and at its original form does not contain any patterns.  Students need to fully understand the structure of this database and the activities it support as a first step.  After that, students are required to identify the types of information needed to support decision purposes using the data stored in the database.  Based on the information required, students then design the structure of a data warehouse so as to better support information retrieval for further analytical tasks.  Most of the tasks required in this project belongs to the planning stage.  Students do not need to fully implement their plans.  However, they should provide evidence on how the proposed data warehouse could be used to achieve the specified goals with a few database tables and some SQL statements and clearly state how the data warehouse design achieves the specified goals which are not attainable without the proposed data warehouse.

Option II: a more managerial option

Amid recent crisis in corporate accounting scandals, you are assigned the job to suggest a better system not only to monitor irregular activities but also to establish better evaluation / performance measures so that chief  executivesare motivated to seek financially and ethically sound objectives.  You may start with the background of the recent incidents involving Enron, Worldcom, and others, analyzing the broad environment that leads to those ffraudulentpractices including but not restricted to accounting system, government regulation, financial market, etc.  You then discuss possible rremediesthat have been implemented or proposed, or your own opinions followed by the design of an intelligent system listing the necessary data needed to be collected, the relationship between different variables, and how early warnings can be signified to alert the management and investors.