Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam 1 Curriculum & Syllabus – 2015 Admission onwards. PGDM – Business Analytics Duration of the Course: 2 Years Full-time (4 semesters) Preamble Following document contains the semester wise course matrices, detailed syllabuses along with credits, breakup of credits in terms of lecture, tutorials and laboratory, assessment pattern, competencies of the courses and sample problems. Specific mention of two projects is also envisaged in the document. Graduate Attributes Need of the PGDM- Business Analytics programme. Most industry sectors have recognized the value that Business Analytics can provide in not only driving Business Solutions, but also in helping them to differentiate themselves to customers, investors and regulators. The global Business Analytics is a USD 105 billion market, growing at a CAGR of 8%. India, with its surfeit of talent, has become the Analytics hub for organizations across the world. Large corporate like Walmart, Target, Citibank, ICICI Bank, Airtel, Vodafone are increasingly adopting analytics in their processes. Consulting giants like PwC, IBM, Accenture, Infosys have large teams offering Analytics solutions to their clients. All of these translate into a huge global and domestic demand for Business Analytics professionals. Employment Potential As per McKinsey Global Institute, the analytics Industry is one of the fastest growing in modern times which is poised to become a $50 billion market by 2017. With this sudden surge in the analytics industry there is a tremendous increase in the demand for analytics expertise across all domains, throughout all major organizations across the globe. It has been predicted that by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions. NASSCOM has estimated that from 50,000 today, the demand for Analytics professionals in India will grow to 2,50,000 in the coming two three years. According to Analytics India Magazine (2013), India will remain the preferred destination for Analytics Outsourcing as compared to other Asian countries like Philippines and China. Unlike the BPO‘s, Analytics (considered as part of KPO) requires skills that are not easily
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Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
1 Curriculum & Syllabus – 2015 Admission onwards.
PGDM – Business Analytics
Duration of the Course: 2 Years Full-time (4 semesters)
Preamble
Following document contains the semester wise course matrices, detailed syllabuses along
with credits, breakup of credits in terms of lecture, tutorials and laboratory, assessment pattern,
competencies of the courses and sample problems. Specific mention of two projects is also
envisaged in the document.
Graduate Attributes
Need of the PGDM- Business Analytics programme.
Most industry sectors have recognized the value that Business Analytics can provide in not
only driving Business Solutions, but also in helping them to differentiate themselves to
customers, investors and regulators. The global Business Analytics is a USD 105 billion
market, growing at a CAGR of 8%. India, with its surfeit of talent, has become the Analytics
hub for organizations across the world. Large corporate like Walmart, Target, Citibank, ICICI
Bank, Airtel, Vodafone are increasingly adopting analytics in their processes. Consulting
giants like PwC, IBM, Accenture, Infosys have large teams offering Analytics solutions to
their clients. All of these translate into a huge global and domestic demand for Business
Analytics professionals.
Employment Potential
As per McKinsey Global Institute, the analytics Industry is one of the fastest growing in
modern times which is poised to become a $50 billion market by 2017. With this sudden surge
in the analytics industry there is a tremendous increase in the demand for analytics expertise
across all domains, throughout all major organizations across the globe. It has been predicted
that by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with
deep analytical skills as well as 1.5 million managers and analysts with the know-how to use
the analysis of big data to make effective decisions.
NASSCOM has estimated that from 50,000 today, the demand for Analytics professionals in
India will grow to 2,50,000 in the coming two three years.
According to Analytics India Magazine (2013), India will remain the preferred destination for
Analytics Outsourcing as compared to other Asian countries like Philippines and China.
Unlike the BPO‘s, Analytics (considered as part of KPO) requires skills that are not easily
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
2 Curriculum & Syllabus – 2015 Admission onwards.
available in these countries. India’s Analytics talent pool will be in high demand because
of their process expertise and English language proficiency.
Major Employers in Business Analytics
There are mainly four types of employers
1. Large IT companies who have an Analytics practice [Example: Accenture, Infosys,
TCS, Wipro]
2. Analytics KPOs [Example: Genpact, WNS]
3. In-House Analytics Units of large corporate [Example: Citibank, Dell, HP, Spencer,
Target]
4. Niche Analytics firms [Example: Cognizant Analytics, AbsolutData, Mu Sigma
Analytics]
Career Opportunities
After learning this programme, student can have following roles in the industry.
Analytics Analyst
Data Analyst / Data Management Analyst
Research Analyst
Reporting & Analytics Lead
Data Scientist
Predictive Analytics Specialist
Data visualizers
Business Analytics Consultant
Data Miner Analytics Manager
Predictive Modelling Analyst
Statistician
Board of Advisors
The programme has been designed under the prudent guidance of following eminent
professionals from industry and academia.
Dr. (Prof) Prithvi Pal Yadav:
A Distinguish Professor of IIM with professional experience of more than two and half
decades.
At present, he is a Director, BIMTECH, Bhubaneswar.
Ex – Acting Director, IIM; Ex- BoG Member, IIM; Member – Senate, IIT; Ex Director,
GHSIMR, Kanpur
Member of BoG, IIM Indore, Subject Matter Expert UPSC, Govt of India
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
3 Curriculum & Syllabus – 2015 Admission onwards.
Teaching premiere institutions in India like IITs, IIMs and foreign universities.
An expert in Data Mining, Business Intelligence Solutions, Six Sigma Applications
and SPSS.
Dr. S.R. Kulkarni:
Ph. D in Statistics; M. Phil in Statistics.
Distinguished Data Scientist at [24]7 Inc., Innovation labs at Bangalore (July 3rd 2011-
Till date); Scientist - Analytics at DataInfoCom (Nov, 2009 to 2012); Manager -
Statistical Research at Cranes Software International Ltd., Bangalore, India (2003 –
2009).
Analytics Experience:
Mining of e-commerce Data
Patents on User Behaviour on websites
Analysis and Design of Experiments(DOE)
Predictive Decision Management Software System for Offline data Mining
Development of algorithms for advanced statistical techniques
Sample surveys and analysis
Dr. Shesha Shah:
MS and PhD in System Science
Co-Founder and Chief Data Scientist at Analytics
Working with global giants, Yahoo, Travelocity and Dell computers in areas of
business intelligence.
18 years of industry experience in the areas of advanced analytics.
Global work experience
Dell Innovator award, 2012
10 Technology Patents
Domain expert in Pattern Recognition, Parallel and distributed algorithms, web data
mining, Statistics, Predictive Modelling, NLP and text processing, Information
retrieval etc.
Dr. (Prof) Nishat:
Base SAS and Stat; Advance SAS, Report and Graph; Advanced Post-Graduate
Diploma in Clinical Research; B.D.S.
5+ years industrial experience in analytics, applied statistics, clinical research.
Given seminars, paper presentation and conducted workshops at University Of New
York, USA and University Of Virginia, USA
Worked intensively in all aspects of SAS including data analysis, database validation;
data cleaning, reporting and applied statistics.
Been teaching since 8 years in various fields of SAS, medical and clinical analytics
subjects.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
4 Curriculum & Syllabus – 2015 Admission onwards.
Curriculum Design of Specialized Two-Year Post Graduate Programme
The programme will train the students in two specific domains. First, they will understand
basic management concepts related to marketing, finance and entrepreneurship and secondly
they will attain the special skill sets for applying Analytics in the management areas.
1. Programme Outcome
The programme will develop a deeper sense about management principles and techniques in
the field of marketing, finance, quantitative analysis and entrepreneurship. They will also
equip themselves with adaptive thinking which is applicable in the management domain.
Students will learn special skill sets for application of Business Analytics in the field of
management. Computational skills are vigorously focussed in the programme.
A reasonable mix of common courses with core courses will make them self-directed on the
path of continuous learning. Core courses will make them capable to apply analytics in
specific areas and then to effectively communicate to the stake holders of given management
challenge.
A good Data Scientist or Business Analyst is supposed to work effectively and efficiently in
the individual capacity and as a team. The programme delivery will in-built these skills and
aptitude.
Students will get the updated knowledge and developments in the field of Analytics by virtue
of interactions with learned industry professionals and academicians.
2. Stages of Curriculum Design
Following section covers the Vision and Mission of the department and that of the institute,
Context of programme and Credits of PG Programme.
2.1 Vision and Mission
Vision of the Department
To be the centre of Commerce and Management Education.
Mission of the Institute
Moulding empowered, committed and socially responsible women leaders.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
5 Curriculum & Syllabus – 2015 Admission onwards.
Objective of the Programme
By virtue of massively enhanced data storage and data retrieval capacity due to technological
advancements in the field of Information Technology, possibility of probing extensively into
the past business information or data has paved the way of new specialized domain called
Business Analytics or Big Data Analytics. Further, the demand of Data Scientists in India and
the World has reached to a level which is difficult to meet through the existing pool of
knowledgeable professionals in this field. This programme is an holistic attempt to create Data
Analysts or Business Analysts for bridging the gap.
Detailed Distribution of Courses and Credits of PG Diploma Program
Name of the Course: Management Concepts and Practices
Duration: One Semester
Semester : 1
Total Lecture Hours: 45 Aim of the Course: The course helps to focus on the concepts and methods of managing an organization. It helps to understand the functioning of an organization, understand the various techniques involved in solving managerial problems. This module is designed
to (i) introduce management and organizational concepts and related theories; (ii) examine the
formulation and implementation of business strategy; and (iii) explain the main management
issues in marketing, human resources, operations and sustainability.
Course Overview and Context: The course gives a brief idea of the nature and characteristics of management and how management functions in an organization. The course tells about the need for planning and also talks about the importance of forecasting and decision making in an organization. It helps in understanding the various types of decision making techniques that managers make use of in taking an important management decision. Syllabus Content Unit 1 11 hours Introduction, Definition of Management, Nature and Characteristics of Management, Management as an Art, Science and Profession , Management and Administration, Levels of Management, Significance and Objectives of Management, Social Responsibility of Management , Management by Objectives (MBO).
Unit 2 9 hours
Fundamentals of Planning, Need for Planning, Definitions of Planning, Planning Process, Components and Types of Planning.
Unit 3 9 hours Forecasting and Decision Making, Importance of Forecasting and Planning, Definitions of Decision Making, Types of Decision Making, Decision Making Techniques, Decision Making Approaches. Unit 4 9 hours Managing Diversity, Meaning and Reasons for Diversity, Managing Diversity in Organizations, Benchmarking Concepts (performance benchmark).
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Semester - 1 Aim of the Course: The aim of the course is to provide an introduction to marketing and understanding its various aspects. The course is designed to serve as an introduction to the theory and practice of marketing. The course also helps students to apply and understand major marketing concepts market segmentation, customer value preposition. Course Overview and Context: The course gives a brief understanding marketing concepts and their application to profit-oriented and non-profit oriented organizations. This course provides an introduction to all aspects of marketing, including strategic marketing planning, marketing research, product planning and development. It provides an understanding of the competitor’s strategies, Characteristics and Classification of products etc. Syllabus Content Unit 1 10 hours Defining Marketing in the Contemporary Context Marketing Concept, Importance of marketing, Scope of marketing, Changes in marketing management in the 21st Century, Tasks necessary for successful marketing management. Developing Marketing Strategies and Plans Customer Value Preposition, Strategic planning process and levels – Corporate planning, Strategic Business Unit planning, Marketing Plan. Components of a modern Marketing Information System, Key methods for tracking and identifying opportunities in the macro-environment, Some important macro-environment developments. Concepts and benefits of Market Segmentation, Variables of Market Segmentation, Identification of appropriate target market for given segment, The positioning strategies of companies’ on the basis of product differentiation. Unit 2 8 hours Competitive Dynamics Analysis of competitors’ strategies, objectives, strengths, and weaknesses, Strategies of market leaders to expand the total market and defend market share, How market challengers attack market leaders.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Unit 3 9 hours Setting Product Strategy Characteristics and Classification of products, Management of product mix and product lines, Packaging, labeling, warranties, and guarantees as marketing tools. Pricing Strategies for Products and services, Adapting prices to meet varying circumstances and opportunities, Initiating a price change, Responding to a competitor’s price challenge. Unit 4 10 hours Designing and Managing Integrated Marketing Channels Designing a Marketing Channel system and value network, Integration of channels and management of channel conflict, Future of e-commerce. Role of Marketing communications, Major steps in developing effective communications, Concept of Communications Mix, Integrated Marketing Communications program. Challenges in developing new products, Organizational structures to manage new-product development, Stages in developing new products, Concept of Diffusion of Innovation. Unit 5 8 hours The Marketing Environment The Emerging Market Environment and implications for Marketing Strategy, Marketing Mix, Marketing Communications, Marketing Budgetting and Marketing ROI’s. Current trends in defining and describing Market Opportunities, Competition, Channels, Media and strategies to monitor, anticipate, manage and drive these for the benefit of our businesses. Competencies of the course C1. Understanding the definition of marketing and the scope of marketing.
C2. Understanding the nature of marketing in the 21st century.
C3. Familiarize with various marketing strategies such as customer value preposition, strategic
planning process.
C4. Understanding the Components of a modern Marketing Information System.
C5. Describe important macro-environment developments.
C6. Understanding the concept of Decision making
C7. Understanding the concept of market segmentation.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Name of the Course: DBMS and Data Warehousing Duration: One Semester Semester - 1
Aim of the Course: The subject gives an understanding on how technology and architecture collaborate together to serve the business requirements of different users in the organization. This subject enables the students to the fundamentals of Data Warehousing and Databases, and how to leverage them for maximising individual and organisational effectiveness. Course Overview and Context: The course predominantly explains the importance of data management in the organization for transactional and analytical objective. This course focuses on the fundamentals of Data Warehousing and Databases. The operational data from database management systems are used for day-to-day business transactions and serve the users on current information specifically whereas the goal of Data Warehousing is to provide the users with homogenized, consistent and comprehensive view of the organization to support planning, forecasting and decision making processes at an enterprise level.
Syllabus Content
Unit 1 12 hours Introduction to Database Management Systems Introduction to databases, the relational model, database design, normalization process, parallel and distributed databases, object oriented databases: concept, web technology and DBMS, transaction management. Unit 2 9 hours Introduction to Data Warehousing Data warehousing concepts, Databases versus Data Warehousing, Business need for data warehousing, architecture of Data Warehouse, building a Data Warehouse, properties of data in Data Warehouse, importance of Meta Data, Data Marts, critical success factors of Data Warehouse, trends in Data Warehousing. Unit 3 9 hours Data Preparation for Data Warehousing Mapping Data Warehouse with Business, dimensional modeling, Data Extraction, Transformation and Loading Tools (ETL), importance of data quality in Data Warehousing.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Unit 4 9 hours Data Warehouse and Analysis Categorizing users of Data Warehouse and their business requirement, reporting and query tools, On-Line Analytical Processing (OLAP) in Data Warehouse, role of Data Warehousing on web applications, introduction to Data Mining, Data Visualization. Unit 5 6 hours Data Warehouse Implementation and Maintenance Introduction to Business Intelligence Applications, expanding Data Warehouse/ Business Intelligence System, deployment, growth and maintenance of Data Warehouse.
Competencies of the course C1. Understand the basics of databases and how to design databases.
C2. Understand transaction management and how it is useful in database management.
C3. Understand the concept of web technology and how it helps in managing databases.
C4. Distinguish databases from data warehousing.
C5. Understand the need for data warehousing by various businesses.
C6. Understand the architecture of Data Warehouse.
C7. Understand the properties of data in Data Warehouse.
C8. Understand the importance of Meta Data and Data Marts.
C9. Identify the critical success factors of Data Warehouse.
C10. Understand the mapping of Data Warehouse with business.
C11. Understand the various applications of Business Intelligence.
C12. Categorize the users of Data Warehouse and their business requirement.
C13. Understand On-Line Analytical Processing (OLAP) in Data Warehouse.
C14. Understand the role of Data Warehousing on web applications.
C15. Understand the importance of data quality in Data Warehousing.
Learning Resources
Mundy, Joy. et al. (2008). The Data Warehouse Lifecycle Toolkit. Indianapolis:
Wiley publishing Inc.
Ponniah, Paulraj. (2011). Data Warehousing: Fundamentals for IT Professionals.
New Delhi: Wiley India Pvt Ltd.
Prabhu, C. S. R. (2008). Data Warehousing: Concepts, Techniques, Products and
Applications. New Delhi: PHI Publications.
Inmon, W. H. (2005). Buidling the Data Warehouse. London: Wiley Publications.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Walkenbach, John. (2010). Excel 2010 Bible. New Delhi: Wiley India Pvt Ltd.
MacDonald, Mathew. (2010). Excel 2010: The Missing Manual. Sebastopol: O'reilly.
Ragsdale, Cliff. T. (2008). Spreadsheet Modelling and Decision Analysis. New York:
Thomson south – western publications.
Monahan, George E. (2000).Management Decision Making: Spread Sheet, Modelling,
Analysis. London: Cambridge University
Blue Print - Question Paper
Module * Part A Part B Part C 1 1 1 1 2 1 1 1 3 1 1 1 4 1 1 1 5 1 1 1 6 1 1 7 1 1 1 8 1 1
PGDM- Business Analytics – CBCSS Exam
First Semester
CO1B05TM - Spreadsheet Modeling and Decision Analysis
Time: 3 hour Maximum Marks: 50
Section A
Answer any 5 questions. Each question carries 1 marks (5 × 1 = 5 marks)
Q1. Give one feature of Ribbon and QAT. Q2. For the below values in cells A1 and B1; Write a function which has two conditions- A1 > 10 and B1 > 5 and returns the value CORRECT or INCORRECT if both are met.
Q3. State whether the statements below are true or false.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Name of the Course: Financial Markets and Instruments
Duration: One Semester
Semester - 2 Aim of the Course: The objective of the course is to help the students to understand the
macro process and system of Indian Financial Markets at the broader level by exposing them
to concepts such as credit creation, productive ventures, money management by government
through RBI, money supply, liquidity, lending, borrowing and facilitation of credit on demand,
issuers and subscribers and generation of income for lenders on short term and long term basis.
The students would be exposed to operations as well as systems and procedures that are
commonly followed in the financial markets which by learning would help them in
understanding the financial markets better.
Course Overview and Context: The course gives a brief understanding of Indian financial system and its structure. It tells about the role of financial sectors in Indian Economy. The course also gives a detailed description of the structure of government securities market, money market and capital market. It talks about the role of government and RBI in the development of financial system. The course gives a detailed insight of the derivatives market in simpler language and also the importance of mutual funds as an investment vehicle. Syllabus Content Unit 1 11 hours Indian Financial System and Structure Financial Markets, Financial Assets, Financial Instruments and Financial Institutions, their role in the development of the financial system, role of government and RBI, money supply, mobilization and channelization, credit creation, utilizing mobilized funds into productive ventures, structure of G-sec market, structure of Money Market and Bond Market, instruments of lending and borrowing in the money market including participants, introduction to CBLO segment, role of Primary Dealers, institutions participation, retail participation, various short term and long term fund raising exercises by various entities on risk-free basis, understanding yield related technicalities. Unit 2 8 hours Primary Market and Public Issue Management: Fund raising practices in the 1980s and 1990s, SEBI regulations on fund raising from public (ICDR Regulations), role of Angel, VC and PE investors, VC and PE exits, public issue and its purpose, types of issues, role of merchant bankers, role of other intermediaries, book building process, bidding process, types of investors, basis of allotments, underwriting, listing formalities. Unit 3 9 hours
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Secondary Markets Role of stock exchanges, role of stockbrokers, secondary market mechanism, type of
participants – traders and investors, index and its utility, risk management by way of
collecting margins, exchange settlement procedures, trading mechanism, pay-offs and
arriving at financial positions, touching upon technical analysis and fundamental
analysis.
Unit 4 8 hours Derivatives Market and Risk Management: Purpose of derivatives, concepts of futures, trading, hedging and arbitrage mechanism, margins and ledger credits, how to protect portfolios from devaluation, touching upon a few options strategies. Unit 5 9 hours Mutual Funds and other instruments Purpose of mutual funds, its structure, fund management basics, type of themes – debt, equity and hybrid themes, mutual fund themes, utility to investors, options available to invest, mutual fund investing v/s direct investing. Competencies of the course C1. Understand the meaning of Financial Markets.
C2. Explain the Structure of Financial System in India
C3. Familiarize with Important Financial Instruments available for investment in India.
C4. Discuss the capital market and money market and its financial instruments.
C5. Familiarize with Industrial securities market and derivatives market operation in India.
C6. Discuss the role role of Domestic Institutional Investors and Foreign Institutional
Investors in Indian financial market
C7. Elucidate RBI functions and organization and its regulatory role in the banking sectors.
C8. Understand the various trading mechanisms and pay-offs.
C9. Understanding the concept of technical and fundamental analysis.
C10. Understand the concept of derivatives.
C11. Understand various hedging and arbitrage mechanisms.
C12. Explain Venture capital role in the economic development of a country
C13. Discuss Stages and features of Venture Capital financing
C14. Understanding the concepts of mutual fund and its structure.
C15. Understanding various types of mutual funds and the purpose of investing in mutual
funds.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Semester - 2 Aim of the Course: The objective of this subject is to familiarise the students with meaning, nature and scope of finance, Valuation of Bonds and Shares, nature of investment decisions, Investment evaluation criteria, Operating and Financial Leverage, significance, theories of Capital Structure, types of Dividend Issues and factors influencing dividend decisions, Working Capital Management, Inventory Management. Course Overview and Context:The course gives an understanding of the concept of Time value of money. It tells about the various methods of valuing bonds and shares and the various types of risks involved in it. The cost gives a snapshot of capital budgeting and discuss about the concept of leverage. The course gives an overall understanding of various theories related to capital structure and dividend decision such M-M hypothesis, Walter’s model etc. Syllabus
Unit 1 8 hours
Overview
Financial Management: Meaning, nature and scope of finance, Time Value of Money, Valuation of Bonds and Shares, Risk and Return, Cost of Capital. Working Capital Management, Inventory Management, Cash Management, Receivables Management.
Unit 2 10 hours
Investment Decision
Capital Budgeting: Nature of investment decisions, Investment evaluation criteria -Net Present Value, Internal Rate of Return, Profitability Index, Payback Period, Discounted Payback Period, Accounting Rate of Return, Capital rationing, Risk analysis in capital budgeting, Statistical techniques, Probability, Expected NPV, Standard deviation and variance and coefficient of Variation, Sensitivity analysis, Scenario Analysis, Simulation Analysis.
Unit 3 10 hours
Financing Decision
Operating and Financial Leverage: Measurement of leverages, Effects of operating and financial leverage on profit, Analysing alternate financial plans, Combined financial and operating leverage, Indifference point, Financial Break Even point.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Capital Structure: Concept, importance and significance, theories of Capital Structure, Net Operating Income Approach, Net Income Approach, Traditional Approach and M.M. Hypotheses – without taxes and with taxes, determining capital structure in practice.
Unit 4 9 hours
Capital Structure and Dividend Decision
Dividend Policies: Concept, types of Dividend issues and factors influencing dividend decisions, Dividend Theories: Irrelevance theory, M-M hypothesis, Relevance Theories: Walter’s model. Gordon’s model, dividend policy in practice, type of dividend policies, stability in dividend policy, corporate dividend behaviour.
Unit 5 8 hours
Exchange Rate Mechanism
Five key relationships, Purchasing Power Parity, Interest rate Parity, Fisher Effect, International Fisher Effect & Forward rate, Currency Arbitrage. Competencies of the course C1. Understand the concept of time value of money.
C2. Explain the valuation of bonds and shares
C3. Familiarize with concepts such as Working Capital Management, Inventory
Management, Cash Management.
C4. Understanding the concept of Capital Budgeting.
C5. Familiarize terms like internal rate of return, profitability index, payback period,
Discounted payback period.
C6. Understanding the risk and return analsysis.
C7. Discuss standard deviation, variance and coefficient of Variation.
C8. Familiarize with various analysis such as Sensitivity analysis, Scenario Analysis,
Simulation Analysis. .
C9. Understanding the concept of leverage and types of leverage.
C10. Understand the importance and significance, theories of Capital Structure, Net
Operating Income Approach, Net Income Approach.
C11. Familiarize with capital structure and dividend decision.
C12. Discuss Walter’s model. Gordon’s model, dividend policy in practice, type of
dividend policies
C13. Understand the concept of purchasing power parity
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Name of the Course: Introduction to Business Analytics Duration: One Semester
Semester - 2 Aim of the Course: The objective of this subject is to provide foundational knowledge associated with the domain of business analytics which will be useful in work environment. The course also aims at making the students aware of the applications of business intelligence. Course Overview and Context: The course familiarizes the students with all concepts of
business intelligence including what problems the technology of Data Warehouse (DW)
/Business Intelligence (BI) /Advanced Analytics (AA) solve for businesses and when an
organisation is ready for DW/BI/AA.
Syllabus Content
Unit 1
IT and Business Analytics 12 hours
Business View of Information Technology Applications, Business Enterprise
Organization, Its Functions, and Core Business Processes, Baldrige Business Excellence
Framework (Optional Reading) , Key Purpose of Using IT in Business, The Connected
World: Characteristics of Internet-ready IT Applications, Enterprise Applications
(ERP/CRM, etc.) and Bespoke IT Applications, Information Users and Their
Requirements.
Unit 2
Digital Data, OLTP and OLAP 12 hours
Types of Digital Data, Getting to Know Structured Data, Getting to Know Unstructured
Data, Getting to Know Semi-Structured Data, Difference Between Semi-Structured and
Structured Data. Introduction to OLTP and OLAP, OLTP (On-Line Transaction
Processing), OLAP (On-Line Analytical Processing), Different OLAP Architectures, OLTP
and OLAP, Data Models for OLTP and OLAP, Role of OLAP Tools in the BI Architecture,
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Should OLAP be Performed Directly on Operational Databases?, A Peek into the OLAP
Operations on Multidimensional Data, Leveraging ERP Data Using Analytics.
Unit 3
Business Intelligence 12 hours
Getting Started with Business Intelligence, Using Analytical Information for Decision
Support, Information Sources Before Dawn of BI?, Business Intelligence (BI) Defined,
Evolution of BI and Role of DSS, EIS, MIS, and Digital Dashboards, Need for BI at Virtually
all Levels, BI for Past, Present, and Future, The BI Value Chain, Introduction to Business
Analytics.BI Definitions and Concepts, BI Component Framework, Who is BI for?, BI
Users, Business Intelligence Applications, BI roles and Responsibilities, popular BI tools.
Unit 4 Data Integration and Modeling 12 hours
Basics of Data Integration, Need for Data Warehouse, Definition of Data Warehouse,
What is a Data Man?, What is Then an ODS?, Ralph Kimball's Approach vs. Who Inmon's
Approach, Goals of a Data Warehouse, What Constitutes a Data Warehouse?, What is
Data Integration?, Data Integration Technologies, Data Quality, Data Profiling.
Multidimensional Data Modeling, Types of Data Model, Data Modeling Techniques, Fact
Table, Dimension Table, Typical Dimensional Models, Dimensional Modeling Life Cycle.
Unit 5
Performance Management and Enterprise Reporting 12 hours
Understanding Measures and Performance Measurement System Terminology, Navigating a Business Enterprise, Role of Metrics, and Metrics Supply Chain "Fact based Decision Making" and KPIS , KPI Usage in Companies, Where Do Business Metrics and KPIS Come From, Connecting the Dots: Measures to Business Decisions. Basics of Enterprise Reporting, Reporting Perspectives Common to All Levels of Enterprise, Report Standardization and Presentation Practices, Enterprise Reporting Characteristics in OLAP World, Balanced Scorecard, Dashboards, How Do You Create Dashboards?, Scorecards vs. Dashboards, The Buzz Behind Analysis.
Competencies of the course C1. Understand the business view of Information Technology Applications.
C2. Understand the key purpose of using IT in business.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Name of the Course: Economic Analysis for Business Decisions
Duration: One Semester
Semester : 3 Aim of the Course: The objective of this subject is to familiarise the students with the basic principles of economics, tools and techniques of Economics and application of the same in the competitive business world. The students will understand the determinants of demand for basic goods, production decisions under various time periods, market structure.
Course Overview and Context
The course gives an understanding of consumer‘s economic activities. It describes the concept
of utility function and the Relationship between consumers Income and spending. The course also helps in understanding the law of demand, law of supply. The course gives a basic understanding of production function, and the cost involved in decision making. The course also talks about the macroeconomic variables involved in business decision.
Syllabus
Unit 1 10 hours Basic Concepts of Economics Economic problems, Flow of economic activities, understanding consumer’s economic behaviour (Utility, Satisfaction, indifference behaviour), Relationship between consumers Income and spending, managerial economics- a way of thinking about business.
Unit 2 10 hours Managing Demand and Supply Law of demand, Understanding the determinants of demand for basic goods, Household durables, Luxuries, Exceptions, Constructing Demand equation, Demand elasticity. Law of Supply, supply determinants, supply equation, concept of Equilibrium. Unit 3 10 hours Production Costs and Business Decision Production function, production decisions under various time periods, scale of production and managerial decision. Types of costs and its significance in decision making, Cost related decisions under various time periods.
Unit 4 8 hours Market Structure Firm under competitive conditions as perfect and imperfect, market characteristics, price and output determination.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Unit 5 7 hours Macro Economics in Business Decision Government and market, National Income computation, Business cycle, inflation, Macroeconomic Policies. Competencies of the course C1. Understand the meaning and concept of economics.
C2. Explain utility function.
C3. Discuss the concept of managerial economics.
C4. Understanding the Relationship between consumers Income and spending.
C5. Understanding the concept of law of demand.
C6. Understanding the determinants of demand for basic goods, Household durables,
Name of the Course: Time Series Econometrics Duration: One Semester Semester - 3 Aim of the Course: By the end of the subject, students should be familiar with Univariate
and multivariate models of stationary and nonstationary time series in the time domain
and be able to develop a comprehensive set of tools and techniques for analyzing various
forms of univariate and multivariate time series.
Course Overview and Context: The Course seeks to cover the various time series
components: Irregular, Seasonal & Cyclic Variations & Trend of Time Series, and the
different models of time series which can be used for analysis .The course also involves
understanding the current literature in applied time series econometrics and survey of
some of the current research topics in time series econometrics.
Syllabus Content
Unit 1
Forecasting Time Series 12 hours
Time Series Components: Irregular, Seasonal & Cyclic Variations & Trend of Time Series;
Forecasting through Averaging and Exponential Smoothing; Holt’s model. Forecasting
C10. Understand the types of error-correction models (estimation and testing).
C11. Understand the relationship between international stock indices.
C12. Understand the concept of downside risk (expected shortfall ES) and credit risk and
its impact.
C13. Understand Value at Risk (VaR) concept and the various methods of calculating VaR.
C14. Distinguish between options implied volatility and GARCH.
C15. Understand ARCH, GARCH, asymmetric GARCH and other extensions.
Learning Resources Hamilton, J. D. (1994). Time Series Analysis. Princeton University Press. Enders, W. (2010). Applied Econometric Time Series. Hoboken, NJ: John Wiley & Sons. Zivot, Eric and Jiahui (Jeffery). (2002). Modeling Financial Time Series with S-PLUS.
Wang: Springer-Verlag.
Brooks, Chris. (2008). Introductory Econometrics for Finance. Cambridge University Press.
Subject: Time Series Econometrics Blue Print - Question Paper
Module * Part A Part B Part C 1 2 1 1 2 1 2 2 3 2 2 1 4 2 1 1 5 1 2 1
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Name of the Course: Predictive Modelling using SAS Duration: One Semester Aim of the Course: By the end of the subject, students should be familiar with the
concepts of a SAS Enterprise Miner project and explore data graphically. Students should
be able to build the predictive models and understand the working of such models. Also
the course will aim at how to generate a score code and how to use it.
Course Overview and Context: The Course seeks to cover the concepts of SAS Enterprise
Miner project . The course involves modifying data for better analysis results, building
and understanding predictive models such as decision trees and regression models,
comparing and explaining complex models, generation of score code and using other
modelling tools such as rule induction, gradient boosting and support vector machines.
Syllabus Content
Unit 1
Introduction 9 hours
Introduction to SAS Enterprise Miner, Accessing and Assaying Prepared Data: Creating a
SAS Enterprise Miner project, library and diagram, Defining a data source, Exploring a
data source.
Unit 2
Introduction to Predictive Modeling with Decision Trees 9 hours
Cultivating decision trees, Optimizing the complexity of decision trees, Understanding
additional diagnostic tools.
Unit 3
Introduction to Predictive Modeling with Neural Networks and Other Modeling
Tools 9 hours
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Course Code : CO4B19TM Name of the Course: Big Data Analytics Duration: One Semester 2:1:0
Aim of the Course: By the end of the course, the student will be able to deploy a
structured lifecycle approach to data science and big data analytics projects. The course
is also designed with the aim that students should be able to select techniques and tools
to analyze big data and create statistical models.
Course Overview and Context: The Course seeks to cover the concepts of big data, the
various techniques and tools available to analyze the big data, creation of statistical
models, the distinguishing factors between Hadoop and BigData. The course also focuses
on Hadoop Distributed File System, its architecture and data flow.
Unit 1
Introduction 9 hours Big Data Overview, Definition with Real Time Examples, How BigData is generated with Real Time Generation, Use of BigData, Future of BigData!, the challenges for processing big data, technologies supporting big data,
Unit 2
Hadoop 9 hours Why Hadoop?, What is Hadoop?, Hadoop vs RDBMS, Hadoop vs BigData, Brief history of Hadoop, Problems with traditional large-scale systems, Requirements for a new approach, Anatomy of a Hadoop cluster
Unit 3
Hadoop Distributed File System (HDFS) 9 hours Concepts & Architecture, Data Flow (File Read , File Write), Fault Tolerance, Shell Commands, Java Base API, Data Flow Archives, Coherency, Data Integrity, Role of Secondary NameNode
HIVE, PIG and HBase 9 hours Architecture, Installation, Configuration, Hive vs RDBMS, Tables, DDL & DML, Partitioning & Bucketing, Hive Web Interface, Why Pig, Use case of Pig, Pig Components
Data Model, Pig Latin
RDBMS Vs NoSQL, HBase Introduction, HBase Components Scanner, Filter Hbase POC, Introduction to MongoDB.
Competencies of the course C1. Understand how Big Data is generated with Real Time Generation.
C2. Understand the challenges for processing big data.
C3. Understand the technologies supporting big data.
C4. Understand the concept of Hadoop.
C5. Distinguish Hadoop with RDBMS and BigData.
C6. Understand the anatomy of a Hadoop cluster.
C7. Understand what Hive Web Interface is.
C8. Distinguish RDBMS with NoSQL.
C9. Understand the architecture, installation, and configuration of HIVE, PIG and HBase.
C10. Understand the need for PIG, its usage and components.
C11. Understand the concept of Hbase, its components scanner and carry out the
filtration for Hbase POC
C12. Understand the concept of MongoDB.
C13. Understand the concept of MapReduce and its data flow.
C14. Distinguish MapReduce APIs with MapRed
C15. Understand the step by step process of programming under MapReduce.
Learning Resources
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Name of the Course: Multivariate data Analysis – 2 Duration: One Semester Aim of the Course: By the end of the subject, students should be able to understand the
theory behind the statistics, Select the appropriate methods in function of the research
question, Apply those methods to their data, Interpret and report the results from the
analysis, Develop critical thinking of statistics.
Course Overview and Context: The Course seeks to cover the concepts of Cluster Analysis,
using cluster analysis as a multivariate technique, the necessity of conceptual support in
Cluster Analysis. The course also focuses on Multidimensional Scaling and MANOVA
analysis and how these tools are useful for decision making process.
Syllabus
Unit 1
Cluster Analysis 9 hours
What is Cluster Analysis, Cluster Analysis as a multivariate technique, conceptual
development with Cluster Analysis, necessity of conceptual support in Cluster Analysis,
how does Cluster Analysis work? Objective versus subjective considerations, Cluster
Analysis decision process, objective of Cluster Analysis, research design in Cluster
Analysis, assumptions in Cluster Analysis, deriving clusters and assessing overall fit,
interpretation of the clusters, validation and profiling of the clusters, an illustrative
example.
Unit 2
Multidimensional Scaling and Correspondence Analysis 9 hours
What is Multidimensional Scaling? MDS works, comparing MDS to other
interdependence techniques, a decision framework for perceptual mapping Overview of
Multidimensional Scaling, Correspondence Analysis, illustrations of MDS and
Correspondence Analysis.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Name of the Course: Data Mining for Business Analytics Duration: One Semester Aim of the Course: The course aims at familiarizing the students with the goals and
objectives of data mining. The main objective of the course is to teach the students how
to conduct a data mining project and obtain practical experience in designing and
implementing data mining algorithms.
Course Overview and Context: The course familiarizes the students with popular
classification techniques, such as decision trees, support vector machines and nearest-
neighbor approaches. The course also includes the most important association analysis
techniques, the complete data mining process and the various methods of data mining.
Data mining software tools will be introduced to students as part of their curriculum.
Syllabus Content Unit 1
Introduction to Data Mining 12 hours
Data Mining for Business Intelligence, Data Mining Goes to Hollywood!, Data Mining
Concepts and Definitions, Definitions, Characteristics, and Benefits, How Data Mining
Works, Data Mining Applications.
Unit 2
Data Mining Process 12 hours
Data Mining Process, Step 1: Business Understanding , Step 2: Data Understanding, Step
3: Data Preparation, Step 4: Modeling Building, Step 5: Testing and Evaluation, Step 6:
Deployment, Other Data Mining Standardized Processes and Methodologies.
Unit 3
Data Mining Methods 12 hours
Data Mining Methods, Classification, Estimating the True Accuracy of Classification
Models, Cluster Analysis for Data Mining.
Unit 4
Artificial Neural Networks 12 hours
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam
Association Rule Mining, Artificial Neural Networks for Data Mining, Elements of ANN,
Applications of ANN.
Unit 5
Data Mining Software Tools 12 hours
Data Mining Software Tools, Data Mining Myths and Blunders.
Competencies of the course C1. Understand Data Mining for Business Intelligence.
C2. Understand how data mining works.
C3. Understand the applications of Data Mining.
C4. Understand the various steps of data mining process.
C5. Understand other data mining standardized processes and methodologies.
C6. Understand the Cluster Analysis for Data Mining.
C7. Understand the methods of Data Mining.
C8. Understand the elements and application of ANN.
C9. Estimate the true accuracy of classification models.
C10. Understand Artificial Neural Networks for Data Mining.
C11. Recognize the data mining myths and blunders.
C12. Understand the Data Mining Software Tools.
C13. Understand the classification of various data mining methods.
C14. Understand Association Rule Mining.
C15. Understand the various characteristics and benefits of data mining.
Learning Resources 1. Turban, Sharda Efraim; Ramesh, Dursun Delen and King, David. (2011). Business
Intelligence: A Managerial Approach, 2nd Edition. Publisher: Prentice Hall.
1. Han, Jiawei and Kamber, Micheline. (2012). Data Mining: Concepts and Techniques,
3rd edition. Morgan Kaufman Publishers.
2. Tang, P.N., Steinback, M. and Kumar, V. (2006). Introduction to Data Mining. Addison
Wesley.
3. Myatt, Glenn and Johnson, Wayne. (2009). Making Sense of Data II. John Wiley& Sons. 4. Rajaraman, Anand. (2011). Mining of Massive Datasets. New York: Cambridge
University Press.
Post Graduate Diploma In Management - Business Analytics St. Teresa’s College (Autonomous), Ernakulam