Data mining for business intelligence answers

Business Intelligence -- Data Mining

Team Project, teams of 3 or 4

Overall Objective: Extend the IDS developed in Project1 to design and develop a BI Portal (or BI Center) for your company. If you want, you can extend the scope of the BI center to include another industry sector (e.g., your company has acquired or merged with another company) or special situation (e.g., a developing country or small island)

PART A: Requirements Definition and Logical Design (20)
· Based on the materials in the textbook, especially the Case Studies in each Chapter, identify at least 10 business problems the BI Center will be able to solve. Be specific (e.g., reduce the customer churn)

· Develop a logical design (conceptual view) of what will be the key components of the BI Center (e.g., the data, the models, analytical tools, data mining tools, etc)

· More grade will be given to deliverables that specifically utilize the textbook materials (especially the case study). For example, if you select text mining, then you should say that “we will use text mining as used by the US Govt for counterterrorism (Opening Vignette, Chapter 7 “Mining Text for Security and Counter Terrorism”).

Important Note: In this assignment, you should rely heavily on the case studies (especially the Opening Vignettes), in Chapters 5-8. Here are the names of these case studies: Chapter 5 “Data Mining Goes to Hollywood!”, Chapter 6 “Predicting Gambling Referenda with Neural Networks”, Chapter 7 “Mining Text for Security and Counter Terrorism”, and Chapter 8“DirecTV Thrives with Active Data Warehousing”

PARTB: Develop a Physical Design of the BI Center (25)
· By searching the Internet, select the tools that you will use in the BI Center (e.g., databases, Excel, data mining tools, analytical tools). Select the “free” tools available on the Internet.

· Pay special attention to the text and web mining, data warehousing and Big Data issues.

· Develop a simple prototype of the BI Center with the selected tools

Hints for tool Selection:

· Use the internet resources and the examples, case studies and sites mentioned in the Text chapters 6 to 9 .

· Further explore expert system tools (e.g., http://www.cs.cofc.edu/~manaris/ai-education-repository/expert-systems-tools.html ) and neural network tools (e.g., http://www.sigma-research.com/bookshelf/rtthinks.htm ) to model and capture knowledge for your case.

· Further explore machine learning tools (e.g. http://www.cs.waikato.ac.nz/ml/weka/index.html ) to improve performance for your particular case.

PART C: Solve Some Real Life Problems (30)
Do any three (the fourth can be an extra credit work)

· Use the BI Center developed in Part B to solve some real life problems (each team member should choose one specific BI problem to solve)

· Add AI, KM and MSS features to the BI Center (use materials from Ch. 11 and 14)

· Customize your BI center to meet the special needs of developing countries and /or small islands.

· Evaluate three real life decision support systems (you will be given access to one, you will have to choose others)

· Use PowerPoint or HTML5 to build one or two simple games that illustrate how business decisions can improve business performance.

Suggestion: You should use the concepts discussed in the following case studies, if possible:

· Ch. 11: MITRE Knows What it Knows through Knowledge Management

· Ch. 11: Siemens Keeps Knowledge Management Blooming with ShareNet

· Ch. 14: Coca Cola RFID-based Dispenser Serves BI

· Ch. 14: Continental Scores Continues to Score With Data Warehouse