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The Business Analytics course offers a comprehensive understanding of key concepts, tools, and techniques essential for data-driven decision-making. It begins with the evolution of business analytics, the analytics process, and an overview of roles like data scientists, data engineers, and business analysts, along with an introduction to R programming. The course delves into data warehousing and mining, covering ETL processes, star schemas, and data mining applications in industries such as retail, healthcare, insurance, and telecommunications. Data visualization is another key focus, teaching students various visualization techniques, cross-tabulation, chart creation, and tools like Tableau, as well as data modelling concepts. The course also explores the three primary types of analytics: descriptive (mean, median, mode, standard deviation), predictive (linear and multivariate regression), and prescriptive (graph analysis, simulation, optimization). By blending theory and practical applications, this course equips students with the skills needed to pursue careers and make data-driven decisions in business.
Dr. Sangeeta Malik holds the position of Professor at the Maharaja Agrasen Institute of Management Studies in Delhi, where she has played a diverse role in accomplishing her career goals. She has been a researcher, educator, trainer, leader, and administrator. Dr. Malik has been an invaluable resource in numerous Faculty Development Programs (FDPs) and Management Development Programs (MDPs), providing expert guidance to various Ph.D. students. Her involvement extends to government research projects, including those funded by ICSSR, and her contributions have even led to patents. With over 26 years of extensive academic involvement in various universities and educational institutions, her expertise spans a broad spectrum. Beyond academia, she is a prolific author with over 25 research papers published in national and international journals. She has been recognized with awards for her excellence in teaching and research within the field of education.
Dr. Sundram Priyadarshnie is currently working as Professor, Head of the BBA department at Bhagwan Parshuram Institute of Technology, (BPIT), New Delhi affiliated to GGSIP University. She did Ph.D in Business administration from Deen Dayal Upadhaya University, Gorakhpur, India. Certification in Advanced HR Analytics from IIM, Rohtak, India. She has more than 21 years of Teaching and Research experience. Her research interests include Management of Finance, Research, Human resource, HR analytics. Many of her research papers have been published in edited books and reputed journals. She has presented papers in national and international conferences. She has also been involved in Consultancy Assignments.
Ms. Neha Garg is currently working as Assistant Professor at Bhagwan Parshuram Institute of Technology (BPIT), New Delhi affiliated to GGSIP University. She has more than three years of teaching experience along with 12 years of rich banking managerial experience. She is pursuing Ph.D. on Artificial Intelligence applications in banking from Bharati Vidyapeeth (Deemed University), Pune. She has completed B.Com(H.) from Ramjas College, Delhi University and Master of Business Administration (MBA) from IBS, Hyderabad. She is UGC-NET qualified. Throughout her academics she has been a ranker and scholarship holder. Her research interest includes Finance, banking, accountancy, research analytics and allied topics. She has written several research papers and book chapters which are published in peer-reviewed, UGC care journals, Scopus indexed journals. She has presented good quality papers in national and international conferences. She is also a reviewer in many journals. She has been a resource person in research FDPs. She is actively taking free awareness sessions on financial literacy in government and private schools, colleges and offices.
1. Introduction to Business Analytics
2. Data Analysis
3. Introduction to R
4. Data Warehousing
5. Data Mining
6. Data Visualisation
7. Descriptive Analytics
8. Diagonistic Analytics
9. Predictive Analytics
10. Prescriptive Analytics
11. Case Studies
Model Test Paper
Glossary
