The massive advances made in computational technologies in recent decades have radically changed the way businesses operate. Data is being increasingly referred to as the new “oil”. Businesses can get access or have access to vast amounts of information about their operations, customers, and products. Interpreting this information to get actionable insights and turn them into productive and profitable business solutions requires trained professionals who are adept at utilizing this data. To meet the burgeoning demand for experts who are skilled in the use of technology, data analysis, and business processes for strategic decision making, the interdisciplinary area of Business Analytics has come into existence.
The Business Analytics specialization offers courses in the disciplines of Business and Data Analytics, Advanced Operations Research, and Enterprise Data Management, besides introducing the student to Big Data and AI and ML. Relevant skill sets are imparted to the students through an appropriate blend of academic and experiential learning. Also, a solid foundation is laid in the application of statistical methods, techniques, and tools to large datasets. The specialization provides students with the background needed to apply statistical methods and techniques through the use of decision support systems (DSS), expert systems (ES), business intelligence (BI) reporting tools, and business analytics (BA) data mining tools. The specialization is built upon a strong and holistic understanding of business areas such as finance, marketing, research methods, accounting, ethics, and entrepreneurship. Graduates will be prepared for business analytics and reporting positions in any industry and also pursue higher education in data science or allied areas.
SPECIALIZATION AIMS
The Business Analytics Major and Minor intends to:
- To be able to mine and extract data from disparate set of sources
- To be able to investigate business transactions and data, especially in the areas of supply chain, marketing, human resources and finance, to establish new relationships and patterns
- To build competency in data analysis, especially the correlation between different variables
- Be able to apply knowledge to business problems and help managers make data-driven decisions
- Be able to identify, formulate, analyze and solve business problems using programming techniques such as Linear and Goal programming
- To build prescriptive and predictive business models
- To be able to confidently use commercial/open-source tools, as well as write custom programs using platforms like Python, as part of problem solution
- To be able to explore areas of application of futuristic techniques such as Artificial Intelligence, Machine Learning, and Natural Language Processing
- To be able to build visual models to enhance interactions during problem-solution discussions, and improve the quality of solutions
SPECIALIZATION OUTCOMES
After successful completion of the Major, the student will be able to:
- Demonstrate basic knowledge in accounting, economics, finance, management, entrepreneurship, and marketing in the application of concepts and theories.
- Integrate the concepts of the core areas of business and apply it in various contexts.
- Understand the importance of ethics in business activities.
- Demonstrate basic knowledge in accounting, economics, finance, management, entrepreneurship, and marketing in the application of concepts and theories.
- Understand the basic concepts of data and its different forms (numbers, text, images, audio etc.)
- Apply methods of extracting relevant data from different sources
- Identify business problems using patterns of data
- Develop an ability to formulate business problems mathematically
- Develop an ability to interpret solutions
- Demonstrate the technical skills required for solving business problems, including using relevant tools/platforms and commercial programming languages
- Identify and apply the knowledge acquired in the classroom on different domains such as supply chain, finance, marketing and human resources
- Articulate research ideas from futuristic topics such as artificial intelligence, machine learning etc.,
- Identify areas of applications of these futuristic topics
After successful completion of the Minor, the student will be able to:
- Develop a sound understanding of the basic concepts of data and its different forms (numbers, text, images, audio etc.)
- Develop a deep understanding of methods of extracting relevant data from different sources
- Develop the ability to identify business problems using patterns of data
- Develop an ability to formulate business problems mathematically
- Develop an ability to interpret solutions
- Demonstrate the technical skills required for solving business problems, including using relevant tools/platforms and commercial programming languages
- Identify and apply the knowledge acquired in the classroom on different domains such as supply chain, finance, marketing and human resources
COURSES (CORE AND ELECTIVE)
30 MAJOR COURSES
| Introduction to Operations Research | Marketing Management | Advanced Operations Research |
| Introduction to Finance and Accounting | Organisational Behaviour | Negotiations |
| Consumer & Markets | Research Methods for Managers | Business Innovation, Entrepreneurship and Strategy |
| Introduction to People Management | Financial Management | Business Applications of Analytics |
| Introduction to Entrepreneurship & Family Business | Introduction to Big Data & Cloud Computing | Machine Learning - 2: Introduction to Deep Learning |
| Introduction to Spreadsheet Modeling | Data Mining for Business Intelligence | Data Analytics Services* |
| Introduction to Quantitative Methods | Design Thinking for Managers | Web and Social Media Analytics* |
| Introduction to Programming | Business Ethics and Corporate Governance | Advanced Analytical Modeling* |
| Managerial Economics | Machine Learning – 1: Introduction | Optimization & Simulation* |
| Accounting for Managers | Statistical Data Analysis and Visualisation | Supply Chain Analytics* |
* 4th year undergraduate courses
Introduction to operations research
The course exposes students to fundamental optimization procedures and techniques to attain skills at structuring business problems and modelling them as a mathematical program, microsoft excel to solve such models, interpret solutions and use the solutions to answer the business problem. The focus of this course will be on applications of quantitative methods in modelling business situations.
Introduction to finance and accounting
The course is aimed at baptizing the students to the vocabularies of accounting theories and practices. Beginning with the accounting concepts, introducing the basic tenets in maintaining the books of accounts, the course finally culminates into the preparation of the financial statements like income statement, balance sheet as well as the cash flow statement. It also covers the bank reconciliation statement and bills of exchange.
Consumers and markets
This course provides a conceptual framework to the students to understand the various dimensions of marketing as a discipline. It focuses on exploring various aspects of marketing, markets, consumers, their shopping behaviour and motivations. It gives broad understanding of the exciting world of shop, shopping and shopper.
Introduction to people management
This course introduces the basic context, concepts and importance of people management in organizations to students. It incorporates application of psychological and sociological concepts to provide understanding about how people work in organizations. The course familiarizes students with the fundamental ideas of organizational behavior and human resource management and prepares them for the advanced courses under the specialisation. It is designed as an essential first course for students of management and entrepreneurship, to familiarise them with the practices of managing people in organizations.
Introduction to entrepreneurship & family business
This course introduces students to entrepreneurship and family businesses. It provides an overview on how they come into being, their perspective on the ecosystem, their mindset and how they manage their enterprises.
Introduction to spreadsheet modelling
This course deals with the use of the spreadsheet to solve managerial problems. It merely highlights the use of microsoft excel as an aid in formulating business problems and invoking appropriate functions to resolve them.
Introduction to quantitative methods
This course is designed to give undergraduate students an introduction to decision making. The use of quantitative techniques is increasingly being adopted in all areas of human endeavour. The need to collect, analyze and interpret mathematical output is increasingly being appreciated for arriving at conclusions or in strategic decision making. This course will deal with fundamental concepts required to model, analyse and solve quantitative problems arising in any discipline. A student undertaking this course can have little to no formal introduction to mathematics and statistics at the higher secondary level.
Managerial economics
This course provides a foundation of economic theories and models for use in managerial decision-making. The course provides students with an overview of theories of demand, supply, production and competition and equips them with the tools and techniques to make effective economic decisions under different business environments.
Accounting for managers
Financial accounting provides the means of recording and reporting financial information in a business. Accounting plays a vital role as an information system for monitoring, problem solving and decision-making. This course provides the fundamentals of financial accounting and goes on to demonstrate how accounting fits into the overall business environment of an organization. In addition to this, management accounting systems, which have a strong internal focus can be effective tools in providing information that is useful in decision making at all levels in the organization. Management accountants play a strategic role in developing and providing both financial and non-financial information that is critical to the success of an organization.
Marketing management
This course provides a conceptual framework to the students to understand the function of marketing in an organization. The course helps students to apply the marketing concepts and theories to solve case studies and projects. The course makes them vigilant of the marketing happenings in the real world and therefore importance of creating effective marketing strategies.
Organisational behavior
This course is an introduction to organizational behaviour for undergraduates. It discusses behaviour in organizations at individual, group & organizational levels and provides an understanding of the underlying aspects that drive behavior. It provides insights into the different theories and their application in the organizational context. It also enables students to understand the utilisation of different tools and practices in directing individual actions towards organizational objectives.
Research methods in management
The objective of the course is to enable students to understand the role and importance of research in improving managerial decisions when faced with uncertainty. Research methods are applied in all functional areas of business viz. Operation management, accounting, finance and marketing. The issue facing managers is not a shortage of information but how to use the available information to make better decisions. Learning this course helps students recognise that data are inherently variable and that the identification measurement, control, and reduction of variation provide opportunities for quality improvement.
Financial management
This course in financial management provides a detailed understanding of the finance function and its interrelationship with other areas of business. It seeks to develop the foundation for financial management concepts. It primarily helps the student to understand how businesses make investment, financing, working capital management and dividend decisions and what are the key factors that influence these decisions.
Design thinking for managers
Design thinking (dt) is a powerful tool to tackle the unstructured & the unknown. Dt is a ‘human centered’ approach to problem solving which emerged at stanford in the 1960’s primarily as a systematic, immersive approach to product design. In recent years, it was found that these approaches can be extended to a wide category of ill-structured, real-world problems, both in emerging and developed markets alike. Dt is getting increasingly popular not only across top corporates, but also in rural, semi-urban and underserved sections of society. Given the diversity of challenges that we face today, it therefore becomes necessary to have thinkers and doers who can focus on addressing such challenges. Dt helps in building those capabilities.
Introduction to big data and cloud computing
This course aims to introduce students to distributed systems designed to process large quantities of data. It provides exposure to analytics frameworks such as Apache Hadoop and Spark which allow programmers to analyze data in cloud platforms. The course will also introduce basic cloud computing concepts and familiarize students with working on virtual machines.
Data mining for business intelligence
The course introduces students to basic techniques of data mining and business analytics. Students will work on extracting business intelligence from business data as well as online sources. The course will introduce analytical as well as predictive models. Finally, data visualization techniques will also be introduced in the course.
Business ethics and corporate governance
The course aims to develop in the student a clear perspective on the role and responsibilities of business in society. It helps the student understand the role of ethics in business. It also dwells on corporate governance frameworks and their relevance to contemporary business environment.
Negotiations
We negotiate every day. We negotiate with potential employers, coworkers, roommates, landlords, parents, bosses, merchants, service providers, spouses, and even our children. What price we want to pay, how much we want to be paid, who will do the dishes … all of these are negotiations. Yet, although people negotiate all the time, most know very little about the strategy and psychology of effective negotiations. Why do we sometimes get our way whereas other times we walk away feeling frustrated by our inability to obtain the agreement we desire? Negotiation is the art and science of securing agreements between two or more interdependent parties. This course is designed to be relevant to a broad spectrum of negotiation problems that are faced by the manager and the professional. It is also designed to complement the technical and diagnostic skills learned in other courses. A basic premise of this course is that while a manager needs analytical skills to develop optimal solutions to problems, a broad array of negotiation skills is needed in order for these solutions to be accepted and implemented.
Machine learning 1: Introduction
This course provides a basic level analysis of machine learning algorithms. This course will introduce supervised learning algorithms such as decision tree learning, support vector machines, and neural networks, unsupervised learning algorithms including k-means and hierarchical clustering. Evaluation of learning algorithms and dimensionality reduction techniques will also be discussed.
Advanced statistics and data visualization
This course prepares the student in advanced techniques of statistics. Business applications generate large amounts of unstructured data. This data needs visualization techniques for ease of interpretation and handling. Further, rigorous statistical analysis is needed to convert it into information , knowledge and models readily applicable to real life applications. This course aims to give students a good understanding of the underlying concepts of statistical data analysis along with data visualization techniques.
Advanced operation research
The course exposes students to advanced optimization techniques to model and solve complex business problems. Microsoft Excel will continue to be used to solve these problems, and the student is expected to have completed the prerequisite courses. The focus of this course will be on applications of quantitative methods in modelling business situations.
Business innovation, entrepreneurship and strategy
The course is designed to expose the student to innovation and its application in entrepreneurship. Today it is the use of innovation in entrepreneurship that makes companies to sustain and pose a threat for competitors. This course will enable students to understand the dynamic nature of the environment and the need for being innovative. In this course, the emphasis is not on filling in frameworks. On the contrary, students will be taught to exhibit unconventional thinking and link it to entrepreneurship. The practical and interwoven theoretical nature of class deliberations will cull out the deeper understanding of entrepreneurship. This course enables a student to understand the role of innovation at different fronts such as product, process, business model etc.
Business applications of analytics
The course will expose the students to business applications of data science & data analytics. Specifically, a student will be able to apply the concepts learnt in lower level classes to an existig business problem. The focus will be on supply chain management domain, but a few general management topics, including finance and marketing will also be taught.
Machine learning - 2: Introduction to deep learning
This course covers introductory aspects of deep learning techniques. Some of the tools we learn are deep learning techniques, including Convolutional networks, RNNs, LSTM , deep auto encoders. Applications of Deep learning to text mining , image and Video Processing will be covered . Applications of deep learning to Business and Social media analytics will also be introduced
23 MINOR COURSES
|
Introduction to Operations Research |
Managerial Economics |
Business Applications of Analytics |
|
Introduction to Finance and Accounting |
Marketing Management |
Machine Learning - 2: Introduction to Deep Learning |
|
Consumer & Markets |
Introduction to Big Data & Cloud Computing |
Data Analytics Services* |
|
Introduction to People Management |
Data Mining for Business Intelligence |
Web and Social Media Analytics* |
|
Introduction to Entrepreneurship & Family Business |
Machine Learning – 1: Introduction |
Advanced Analytical Modeling* |
|
Introduction to Spreadsheet Modeling |
Statistical Data Analysis and Visualisation |
Optimization & Simulation* |
|
Introduction to Quantitative Methods |
Advanced Operations Research |
Supply Chain Analytics* |
|
Introduction to Programming |
Business Innovation, Entrepreneurship and Strategy |
* 4th year undergraduate courses
Introduction to operations research
The course exposes students to fundamental optimization procedures and techniques to attain skills at structuring business problems and modelling them as a mathematical program, microsoft excel to solve such models, interpret solutions and use the solutions to answer the business problem. The focus of this course will be on applications of quantitative methods in modelling business situations.
Introduction to finance and accounting
The course is aimed at baptizing the students to the vocabularies of accounting theories and practices. Beginning with the accounting concepts, introducing the basic tenets in maintaining the books of accounts, the course finally culminates into the preparation of the financial statements like income statement, balance sheet as well as the cash flow statement. It also covers the bank reconciliation statement and bills of exchange.
Consumers and markets
This course provides a conceptual framework to the students to understand the various dimensions of marketing as a discipline. It focuses on exploring various aspects of marketing, markets, consumers, their shopping behaviour and motivations. It gives broad understanding of the exciting world of shop, shopping and shopper.
Introduction to people management
This course introduces the basic context, concepts and importance of people management in organizations to students. It incorporates application of psychological and sociological concepts to provide understanding about how people work in organizations. The course familiarizes students with the fundamental ideas of organizational behavior and human resource management and prepares them for the advanced courses under the specialisation. It is designed as an essential first course for students of management and entrepreneurship, to familiarise them with the practices of managing people in organizations.
Introduction to entrepreneurship & family business
This course introduces students to entrepreneurship and family businesses. It provides an overview on how they come into being, their perspective on the ecosystem, their mindset and how they manage their enterprises.
Introduction to spreadsheet modelling
This course deals with the use of the spreadsheet to solve managerial problems. It merely highlights the use of microsoft excel as an aid in formulating business problems and invoking appropriate functions to resolve them.
Introduction to quantitative methods
This course is designed to give undergraduate students an introduction to decision making. The use of quantitative techniques is increasingly being adopted in all areas of human endeavour. The need to collect, analyze and interpret mathematical output is increasingly being appreciated for arriving at conclusions or in strategic decision making. This course will deal with fundamental concepts required to model, analyse and solve quantitative problems arising in any discipline. A student undertaking this course can have little to no formal introduction to mathematics and statistics at the higher secondary level.
Managerial economics
This course provides a foundation of economic theories and models for use in managerial decision-making. The course provides students with an overview of theories of demand, supply, production and competition and equips them with the tools and techniques to make effective economic decisions under different business environments.
Marketing management
This course provides a conceptual framework to the students to understand the function of marketing in an organization. The course helps students to apply the marketing concepts and theories to solve case studies and projects. The course makes them vigilant of the marketing happenings in the real world and therefore importance of creating effective marketing strategies.
Introduction to big data and cloud computing
This course aims to introduce students to distributed systems designed to process large quantities of data. It provides exposure to analytics frameworks such as Apache Hadoop and Spark which allow programmers to analyze data in cloud platforms. The course will also introduce basic cloud computing concepts and familiarize students with working on virtual machines.
Data mining for business intelligence
The course introduces students to basic techniques of data mining and business analytics. Students will work on extracting business intelligence from business data as well as online sources. The course will introduce analytical as well as predictive models. Finally, data visualization techniques will also be introduced in the course.
Machine learning 1: Introduction
This course provides a basic level analysis of machine learning algorithms. This course will introduce supervised learning algorithms such as decision tree learning, support vector machines, and neural networks, unsupervised learning algorithms including k-means and hierarchical clustering. Evaluation of learning algorithms and dimensionality reduction techniques will also be discussed.
Advanced operation research
The course exposes students to advanced optimization techniques to model and solve complex business problems. Microsoft Excel will continue to be used to solve these problems, and the student is expected to have completed the prerequisite courses. The focus of this course will be on applications of quantitative methods in modelling business situations.
Business innovation, entrepreneurship and strategy
The course is designed to expose the student to innovation and its application in entrepreneurship. Today it is the use of innovation in entrepreneurship that makes companies to sustain and pose a threat for competitors. This course will enable students to understand the dynamic nature of the environment and the need for being innovative. In this course, the emphasis is not on filling in frameworks. On the contrary, students will be taught to exhibit unconventional thinking and link it to entrepreneurship. The practical and interwoven theoretical nature of class deliberations will cull out the deeper understanding of entrepreneurship. This course enables a student to understand the role of innovation at different fronts such as product, process, business model etc.
Business applications of analytics
The course will expose the students to business applications of data science & data analytics. Specifically, a student will be able to apply the concepts learnt in lower level classes to an existig business problem. The focus will be on supply chain management domain, but a few general management topics, including finance and marketing will also be taught.
Machine learning - 2: Introduction to deep learning
This course covers introductory aspects of deep learning techniques. Some of the tools we learn are deep learning techniques, including Convolutional networks, RNNs, LSTM , deep auto encoders. Applications of Deep learning to text mining , image and Video Processing will be covered . Applications of deep learning to Business and Social media analytics will also be introduced