LM Thapar School of Management, Chandigarh, Associate Professor: Dr. Sandeep Goyal Interview

Dr. Sandeep Goyal is the Associate Professor of LM Thapar School of Management, Chandigarh. He has done B.E(Computer Science and Engineering) from Punjab Engineering College, Chandigarh. In addition to this, he has completed Post Graduate Program, from Management Development Institute, Gurgaon along with certifications like Six Sigma Black Belt, and IT Service Management from EXIN International, the Netherlands. Dr. S. Goyal & B.S. Sergi has written a book - Towards a Theory of" Smart" Social Infrastructures at Base of the Pyramid: A Study of India, a book published by Cambridge University Press. There are more than 30 refereed Journal Publications and Teaching Cases published under his name. He also participated in several industry workshops and conferences in Toronto, USA, and India. Apart from this, he also has more than 425 Google citations. 

What is the latest course/specialization that you are offering in your institute/dept, which will help students outperform and stand apart from the crowd? 

LM Thapar School of Management offers a two-year full-time MBA program with an option to choose among ten specializations. Our program aims to develop globally sensitive, scholarly practitioners with a social entrepreneurial mindset. All the specializations offered at LMTSM are designed to cater to the demands of the industry, and specifically, the dual specialization arrangement inculcates flexibility in students to be able to follow career paths as per emerging trends and requirements in the corporate world.

One of the specializations that LM Thapar School of Management has commenced with great zeal to meet the soaring / trending demand in the market is MBA - Business Analytics and Big Data (BABD). 

Over 90% of the world's data has been generated in the last few years. Considering the humongous amount of data generation, it has become a critical corporate asset and competitive advantage for companies everywhere. This has led to a massive increase in demand for data analytics professionals across companies globally. 

What are the factors that make this program the best for the students to opt for? 

Several factors make big data and business analytics programs an attractive choice for students:

1. High demand: With the rise of data-driven decision-making in businesses across industries, there is a high demand for professionals with skills in big data and analytics.
2. Innovative mindset: The insights that one can draw leveraging business analytics and big data are a roadmap to innovate and improve.
3. Career opportunities: The job market for individuals with a big data and analytics background is strong and growing. Graduates of these programs can find employment in various industries, including finance, healthcare, marketing, and technology.
4. Competitive salaries: Professionals with skills in big data and analytics typically earn high salaries due to their specialized skill set and the demand for their services.
5. Interdisciplinary nature: Big Data and analytics programs often combine elements of computer science, statistics, and business, providing students with a well-rounded education that can be applied in a variety of fields.
6. Advancements in technology: The field of big data and analytics is constantly evolving as new technologies emerge. Students who choose this field will have the opportunity to work with cutting-edge tools and techniques.
7. Personal interest: Students who are passionate about data, technology, and problem-solving may find big data and analytics to be a natural fit for their skills and interests.

Overall, the combination of high demand, career opportunities, competitive salaries, interdisciplinary education, technological advancements, and personal interest make big data and business analytics programs an excellent choice for students seeking a career in a growing and dynamic field.

What will you say are the “best practices” in the course that you are offering? 

The ability to communicate insights derived from data analysis is essential. The business analytics & big data course emphasizes skills in data visualization, storytelling, and effective communication.

Students get opportunities to work with real-world data sets and use industry-standard tools to gain practical experience in data analysis.

Business Analytics and Big Data course projects require collaboration among team members with different skill sets. Collaborating with peers can help students develop essential teamwork and communication skills.

It is essential to have a solid foundation in statistics, computer programming, and data analysis to succeed in business analytics and big data. This course ensures developing a strong understanding of these fundamentals before diving into more advanced topics.

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What are some valuable insights about the course that you are offering at your institute/dept.? 

This specialization aims at developing the competencies amongst data analytic students to:

• Learn how to extract, transform, load, and integrate huge volumes of different data types to build and deploy machine learning models.
• Understand key analytic programming languages and their application in deriving analytic outcomes for different business scenarios.
• Develop skills in creating machine learning models to deal with real-world problems
• Appreciate the importance of contemporary developments in the analytics domain and their impact on business and society today and in the future.

How does the program ensure students are prepared for the future? 

Business Analytics & Big Data specialization provides an opportunity for students who want to gain expertise and build careers in business analytics and big data discipline. Students will learn how to analyze the large volume of structured and unstructured data to make informed business decisions in marketing, human resource, finance, and operations. Students will develop an analytic mindset and data-oriented skills in this course.

How did you train yourself/faculty to deliver this program to the students? 

Faculty use various pedagogical tools like case discussion and analysis, flipped classrooms, video interventions, problem-solving, in-class tests, tutorials, etc., for a more engaged teaching and learning process. The brighter students are encouraged to play an essential role in the teaching and learning process by taking over the class in any case discussion or flipped classroom setup. Most core courses of three credits have two lectures and one tutorial class every week. Students are divided into smaller groups for the tutorial class. The tutorial class allows the faculty to revise the concepts taught in the lecture and do extra problems with the students to improve their understanding. The weaker students can raise doubts and queries in the small group tutorial classes.

How do you tend to build an industry connection with this program? 

An industry connection is a lasting relationship and should be two-way traffic. We tend to develop, nurture and improve industry connections, and make it a fulfilling association for both ends. The industry partners should benefit from the association, and students should be able to derive as much experience and value as possible. 

Some of the most successful models of industry connect for this program are – Student internships, consultancy projects, research projects, case studies, engagement in hosting and conducting industry events, conferences, workshops, and seminars, and in-practice course fulfillment with the industry partners.

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What challenges did you face while inculcating this program into your curriculum? 

Inter-disciplinary content is one of the key requirements in any good Business Analytics program. This implies a good Analytics program needs to blend the courses from Statistics, Management, and Computer Science areas. Getting the rights experts with these skills and integrating these courses in a seamless manner is a challenge, which we faced at the beginning at our end as well. However, being a university having expertise in the disciplines of computer science, management, and mathematics, we minimized this challenge by leveraging our interdisciplinary strengths in offering this specialization.

Another challenge involves the industry interface for project-based learning. The majority of the faculties taking up courses for analytics students have prior industry experience in IT companies in India. So, these faculties are adding a lot of value in enabling experience / project-based learning of analytics subjects among the students.