| IT6010 | BUSINESS INTELLIGENCE | L T | P C |
| 3 0 | 0 3 |
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.
UNIT II KNOWLEDGE DELIVERY 9
The business intelligence user types, Standard reports, Interactive Analysis and Ad Hoc Querying, Parameterized Reports and Self-Service Reporting, dimensional analysis, Alerts/Notifications, Visualization: Charts, Graphs, Widgets, Scorecards and Dashboards, Geographic Visualization, Integrated Analytics, Considerations: Optimizing the Presentation for the Right Message.
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
UNIT IV BUSINESS INTELLIGENCE APPLICATIONS 9
Marketing models – Logistic and Production models – Case studies.
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.
TOTAL: 45 PERIODS
OUTCOMES:
At the end of the course the students will be able to
- Explain the fundamentals of business intelligence.
- Link data mining with business intelligence.
- Apply various modeling techniques.
- Explain the data analysis and knowledge delivery stages.
- Apply business intelligence methods to various situations.
- Decide on appropriate technique.
TEXT BOOK:
- Efraim Turban, Ramesh Sharda, Dursun Delen, “Decision Support and Business Intelligence
REFERENCES:
- Larissa T. Moss, S. Atre, “Business Intelligence Roadmap: The Complete Project Lifecycle of
- Carlo Vercellis, “Business Intelligence: Data Mining and Optimization for Decision Making”, Wiley
- David Loshin Morgan, Kaufman, “Business Intelligence: The Savvy Manager?s Guide”, Second
- Cindi Howson, “Successful Business Intelligence: Secrets to Making BI a Killer App”, McGraw- Hill, 2007.
- Ralph Kimball , Margy Ross , Warren Thornthwaite, Joy Mundy, Bob Becker, “The Data
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