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Business Analytics BAD714B

Business-Analytics-BAD714B

Downlaod vtu notes, model paper, previous year paper of Business Analytics BAD714B for 7th semester 2022 scheme..

Business Analytics BAD714B

Course Code: BAD714B

Credits: 03

CIE Marks: 50

SEE Marks: 50

Total Marks: 100

Exam Hours: 03

Total Hours of Pedagogy: 40H

Teaching Hours/Weeks: [L:T:P:S] 3:0:0:0

An Overview of Business Intelligence, Analytics, Data Science, and AI: Changing Business Environments and Evolving Needs for Decision Support and Analytics, Decision-Making Processes and Computerized Decision Support Framework, Evolution of Computerized Decision Support to Analytics/Data Science, A Framework for Business Intelligence, Analytics Overview.

Artificial Intelligence – Concepts, Drivers, Major Technologies, and Business Applications: Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications, Conversational AI—Chatbots.

Descriptive Analytics I -Nature of Data, Big Data, and Statistical Modeling: The Nature of Data in Analytics, A Simple Taxonomy of Data, The Art and Science of Data Preprocessing, Definition of Big Data, Fundamentals of Big Data Analytics, Big Data Technologies, Big Data and Stream Analytics, Statistical Modeling for Business Analytics, Regression Modeling for Inferential Statistics.

Descriptive Analytics II: Business Intelligence Data Warehousing, and Visualization: Business Intelligence and Data Warehousing, Data Warehousing Process, Data Warehousing Architectures, Data Management and Warehouse Development, Data Warehouse Administration, Security Issues, and Future Trends, Business Reporting, Data Visualization, Different Types of Charts and Graphs, The Emergence of Visual Analytics, Information Dashboards.

Predictive Analytics I – Data mining process, methods, and Algorithms: Data Mining Concepts and Applications, Data Mining Applications, Data Mining Process, Data Mining Methods.

Prescriptive Analytics – Optimization and Simulation: Model-Based Decision-Making, Structure of Mathematical Models for Decision Support, Certainty, Uncertainty, and Risk, Decision Modeling with Spreadsheets.

Predictive Analytics II – Text, Web, and Social Media Analytics: Text Analytics and Text Mining Overview, Natural Language Processing (NLP), Text Mining Applications, Text Mining Process, Sentiment Analysis and Topic Modeling, Web Mining Overview, Search Engines, Web Usage Mining (Web Analytics), Social Analytics.

2022 SCHEME QUESTION PAPER

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