Syllabus - Business Intelligence (Departmental Elective-702 (B))

Introduction to Business Intelligence

Syllabus Business Intelligence (BI), Scope of BI solutions and their fitting into existing infrastructure, BI Components, Future of Business Intelligence, Functional areas and description of BI tools, Data mining & warehouse, OLAP, Drawing insights from data: DIKW pyramid Business Analytics project methodology - detailed description of each phase.

Business Intelligence Implementation

Key Drivers, Key Performance Metrics, BI Architecture/Framework, Best Practices, Business Decision Making, Styles of BI-vent-Driven alerts – A cyclic process of Intelligence Creation, Ethics of Business Intelligence. Performance Indicators and

Decision Support System

Representation of decision-making system, evolution of information system, definition and development of decision support system, Decision Taxonomy Principles of Decision Management Systems.

Analysis & Visualization

Definition and applications of data mining, data mining process, analysis methodologies, Typical pre-processing operations: combining values into one, handling incomplete or incorrect data, handling missing values, recoding values, sub setting, sorting, transforming scale, determining percentiles, data manipulation, removing noise, removing inconsistencies, transformations, standardizing, normalizing,min-max normalization, z-score. standardization, rules of standardizing data. Role of visualization in analytics, different techniques for visualizing data.

Business Intelligence Applications

Marketing models: Relational marketing, Salesforce management, Business case studies, supplychain optimization, optimization models for logistics planning, revenue management system.