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OIT1703 BUSINESS INTELLIGENCE L T P C
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OBJECTIVES:

The student should be made to

 Be exposed with the basic rudiments of business intelligence system
 understand the modeling aspects behind Business Intelligence
 understand of the business intelligence life cycle and the techniques used in it
 Be exposed with different data analysis tools and techniques

UNIT I BUSINESS INTELLIGENCE 9

Effective and timely decisions – Data, information and knowledge – Role of mathematical models –
Business intelligence architectures: Cycle of a business intelligence analysis – Enabling factors in
business intelligence projects – Development of a business intelligence system – Ethics and business
intelligence. ( Ref. Book 1: Chapter 1)

UNIT II MATHEMATICAL MODELS AND METHODS 9

Mathematical models for decision making-Data mining-Data preparation-Data exploration-Regression-
Time series-Classification-Association rules-Clustering (Ref. Book 1: Chapter 4-12)

UNIT III EFFICIENCY 9

Efficiency measures – The CCR model: Definition of target objectives- Peer groups – Identification of
good operating practices; cross efficiency analysis – virtual inputs and outputs – Other models. Pattern
matching – cluster analysis, outlier analysis (Ref. Book 1: Chapter 15)

UNIT IV BUSINESS INTELLIGENCE APPLICATIONS 9

Marketing models – Logistic and Production models – Case studies. (Ref. Book 1: Chapter 13 and 14)

UNIT V FUTURE OF BUSINESS INTELLIGENCE 9

Future of business intelligence – Emerging Technologies, Machine Learning, Predicting the Future, BI
Search & Text Analytics – Advanced Visualization – Rich Report, Future beyond Technology
(Ref. Book 1: Chapter 14)
TOTAL: 45 PERIODS

OUTCOMES:
At the end of the course the students will be able to
1. Explain the fundamentals of business intelligence.
2. Link data mining with business intelligence.
3. Apply various modeling techniques.
4. Explain the data analysis and knowledge delivery stages.
5. Apply business intelligence methods to various situations.
6. Decide on appropriate technique.

Curriculum and Syllabus | Open Electives | R 2017 | REC Page 73