Information Management - MB25102

MB25102:

Information Management

Course Objectives:

This course equips the foundational and advanced knowledge of how information systems contribute to strategic Business decisions and operations. It introduces the key concepts of data, system design, databases, and information security and integrates recent IT advancements such as AI, IoT, blockchain, and quantum computing.

Fundamentals of Information Systems in Business: Data, Information, Information System, evolution, types based on functions and hierarchy, Enterprise and functional information systems.

Systems Analysis and Design Techniques: The work of a system analyst- SDLC-System design, AGILE Model, Waterfall Model, Spiral Model, Iterative and Incremental Model - RAD Model - Requirement analysis - Data flow diagram, relationship diagram, UML diagram, design-Implementation-Evaluation and maintenance of MIS, Database System: Overview of Database-Components-advantages and disadvantages of database; Data Warehousing and Data Mining; Business Intelligence; Artificial Intelligence; Expert System; Big Data; Cyber Safety and Security-Cryptography; RSA Model of Encryption; Data Science - Block Chain Technology; E-commerce and E-Business models; IOT - RFID.

Database Management Systems and Warehousing: DBMS, types and evolution, RDBMS, OODBMS, RODBMS, Data warehousing, Data Mart, Data mining - Association rule mining - Clustering - Pattern matching.

Integrated Systems and Information Security: Knowledge based decision support systems, Integrating social media and mobile technologies in Information system, Security, IS Vulnerability, Disaster Management, Computer Crimes, Securing the Web.

Emerging Information Technologies: Machine learning - Deep learning, Big data, Pervasive Computing, Cloud computing, Advancements in AI, IoT, Block chain, Crypto currency, Quantum computing

Managerial Applications and Strategic Use: Strategic role of IT in Business, Role of CIO and IT governance, Aligning IT with Business objectives, Legal and ethical issues in information management, Technology adoption models, IT project management, Role of information systems in Business analytics and decision science.

Weightage: Continuous Assessment: 40%, End Semester Examinations: 60%.

Assessment Methodology: Written Test I & II (60%) Assignment, Presentation, Case Study, Quiz, Simulation, Online Certification, Seminar, Mini project (40%)

References:

1. Laudon, K. C., & Laudon, J. P. (2022). Management information systems (17th ed.). Pearson.

2. Schultheis, R., & Sumner, M. Management information systems – The manager’s view. Tata McGraw Hill.

3. (Note: No edition/year available; if you find one, I can update it.)

4. Panneerselvam, R. (2018). Database management systems (3rd ed.). PHI Learning.

5. Laudon, K. C., Turban, E., & Traver, C. G. (2023). E-commerce: Business, technology, society (17th ed.). Pearson.

6. Loshin, D. (2021). Big data analytics (2nd ed.). Elsevier.

7. Han, J., Kamber, M., & Pei, J. (2012). Data mining: Concepts and techniques (3rd ed.).