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Subject Syllabus

AD-702 (B) - Business Intelligence

AIDS · Semester 7

Course Modules

Learn topic-wise with Hyper AI and revise using mapped PYQs.

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.

Key Drivers Key Performance Indicators and 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.

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

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.

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