Program

Master of Business Administration in Business Intelligence

Program Code

MBABI

Level

Post Graduate

Duration

2 Year

Department name

Department of Business Intelligence
Semester Sr no CourseCode Course CourseCredit
Sem-1 1 BI-101 Principles of Management (PoM) 4
Sem-1 2 BI-102 Financial Accounting for Managers (FAM) 4
Sem-1 3 BI-103 Business Communications & Etiquettes (BCE) 4
Sem-1 4 BI-104 Information Systems for Management (ISM) 4
Sem-1 5 BI-105 Applied Statistics for Decision Making (ASDM) 4
Sem-1 6 BI-106 Basics of Business Analytics (BBA) 4
Sem-1 7 BI-107 Data Analysis using Spreadsheet (DAS) 4
Sem-1 8 BI-108 Tableau For Business Analytics (TBA) 4
Sem-2 1 BI-201 Marketing Management (MM) 4
Sem-2 2 BI-202 Behavioural Sciences and Human Resource Management (BS & HRM) 4
Sem-2 3 BI-203 Corporate Finance (CF) 4
Sem-2 4 BI-204 Data Analysis using SPSS (DA_SPSS) 4
Sem-2 5 BI-205 Qualitative Data Analysis (QDA) 4
Sem-2 6 BI-206 Foundation of Econometrics (FoE) 4
Sem-2 7 BI-207 Business Research & Analytics (BRA) 4
Sem-2 8 BI-208 Digital Designing Skill and Digital Marketing (DDS & DM) 4
Sem-3 1 BI-301 Multivariate Statistical Analysis (MSA) 4
Sem-3 2 BI-302 Python For Business Analytics (PBA) 4
Sem-3 3 BI-303 Foundation of Data Management in R (FDM) 4
Sem-3 4 BI-304 Contemporary issues in Business Analytics (CIBA) 4
Sem-3 5 BI-E101 Employment Enhancement Skills (EES) 4
Sem-3 6 BI-E102 Fundamentals of Machine Learning (FML) 4
Sem-3 7 BI-E103 Supply Chain And Logistics Analytics (SC & LA) 4
Sem-3 8 BI-E104 Marketing, Web and Social Media Analytics (MW & SMA) 4
Sem-3 9 BI-E105 HR Analytics (HRA) 4
Sem-3 10 BI-E106 Healthcare Analytics (HA) 4
Sem-3 11 BI-E107 Financial Analysis & Reporting (FAR) 4
Sem-3 12 BI-E108 Fraud And Risk Analytics (FRA) 4
Sem-4 1 BI-401 Summer Internship Programme 6 to 8 Weeks after First MBA-I (SIP) 2
Sem-4 2 BI-402 Special Study Report (SSR) 4
Sem-4 3 BI-403 On-site Project Training / On Job Training 4 to 5 Months (Long Term) Dissertation Project Report (DPR) 6
Intake
Eligibility Criteria
  • PO1: Programme Outcomes: On successful completion of the programme, students will be able to : 1. Exhibit a deep understanding of core business intelligence principles and practices, effectively applying them to solve real-world organizational challenges. 2. Showcase skills in advanced data analysis techniques and tools, capable of interpreting complex datasets and presenting insights through effective visualizations. 3. Utilize strategic thinking and critical analysis to address complex business problems, creating innovative and practical recommendations. 4. Communicate complex analytical findings and strategic recommendations clearly and professionally to diverse stakeholders through reports and presentations. 5. Adhere to ethical standards and regulatory requirements in data handling and business intelligence, ensuring responsible and compliant decision-making. 6. Demonstrate strong leadership and collaboration skills, effectively managing BI projects and contributing to team and organizational goals. 7. Acquire valuable industry insights and practical experience, preparing them for leadership roles in business intelligence through internships and real-world projects. The courses available in this program are meticulously crafted, regularly revised, and thoroughly reviewed by experts from both industry and academia. This process incorporates invaluable insights to ensure that the curriculum reflects contemporary management principles and practices. By integrating current industry trends and academic advancements, the program provides a comprehensive and up-to-date education in management.
  • PSO1: PROGRAMME SPECIFIC OUTCOMES (PSOs): No. PROGRAMME SPECIFIC OUTCOMES PSO - 01 Gather, process, and analyze data to support business decisions. PSO - 02 Apply BI insights to formulate and implement effective business strategies. PSO - 03 Master contemporary BI tools and technologies for data analysis and visualization. PSO - 04 Lead BI projects and teams, ensuring successful execution and stakeholder communication. PSO - 05 Manage business data responsibly, adhering to legal and ethical standards. PSO - 06 Communicate BI findings and business recommendations to diverse audiences. PSO - 07 Develop creative, data-driven solutions to complex business problems. PSO - 08 Manage resources and timelines for successful BI project outcomes.
Subject Name: Principles of Management (PoM)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Develop understanding of key concepts related to business, profession, and management. K2 (UNDERSTAND) CO 2: Explain the importance of business organization and management processes. K3 (APPLY) CO 3: Use planning and decision-making models in practical scenarios. K4 (ANALYZE) CO 4: Differentiate between types of organizational structures and decision-making processes. K5 (EVALUATE) CO 5: Assess the effectiveness of different management theories and control mechanisms. K6 (CREATE) CO 6: Design comprehensive business plans, organizational structures, and management strategies based on theoretical knowledge and case study analysis.

Subject Name: Financial Accounting for Managers (FAM)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Explain the role of accounting as an information system in businesses and how it supports decision-making. K2 (UNDERSTAND) CO 2: Analyze balance sheets and profit & loss accounts to assess the financial health and performance of a business. K3 (APPLY) CO 3: Apply basic accounting mechanics to prepare accurate financial statements, including journals, ledgers, and trial balances. K4 (ANALYZE) CO 4: Evaluate different methods of revenue recognition and measurement, and assess their impact on financial statements. K5 (EVALUATE) CO 5: Demonstrate knowledge of accounting for fixed and intangible assets, including the calculation and reporting of depreciation and amortization. K6 (CREATE) CO 6: Analyze cash flow statements to determine the cash generation, utilization, and financial flexibility of a business.

Subject Name: Business Communications & Etiquettes (BCE)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Define key concepts in communication and comprehend fundamental communication concepts. K2 (UNDERSTAND) CO 2: Identify common roadblocks and the role of verbal and non-verbal symbols in communication. K3 (APPLY) CO 3: Discover the characteristics of good listening, recognize poor listening habits, and demonstrate effective listening skills through role plays and practical exercises. K4 (ANALYZE) CO 4: Analyze different barriers to effective communication and evaluate strategies to overcome these barriers to enhance communication efficacy. K5 (EVALUATE) CO 5: Engage in group discussions, mock interviews, and meetings, applying effective strategies for conducting these activities, and evaluating their performance and outcomes. K6 (CREATE) CO 6: Create professional business documents, including letters, memos, emails, reports, and proposals.

Subject Name: Information Systems for Management (ISM)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Define fundamental terms and concepts related to computers and networking, including computer definitions, software types, system characteristics, and network components. K2 (UNDERSTAND) CO 2: Demonstrate comprehension of basic principles in computer systems and networking, encompassing application software roles, internet functionalities like browsing and emailing, and fundamental security measures. K3 (APPLY) CO 3: Apply acquired knowledge to execute basic tasks in computer systems and networking, utilizing operating systems, internet functions, and implementing rudimentary security protocols. K4 (ANALYZE) CO 4: Analyze the components and operations of Management Information Systems (MIS), evaluating their structures and assessing decision-making processes in the context of information management. K5 (EVALUATE) CO 5: Assess the impact and potential of E-Commerce on traditional commerce, critically examining its advantages, limitations, and diverse business models like B2C, B2B, and C2C. K6 (CREATE) CO 6: Synthesize E-Commerce knowledge to develop innovative solutions for business challenges, creating strategic plans for the implementation and security of E-Commerce transactions.

Subject Name: Applied Statistics for Decision Making (ASDM)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Recall fundamental statistical concepts, terminology, and formulas, including measures of central tendency, variability, probability distributions, and hypothesis testing methods. K2 (UNDERSTAND) CO 2: Demonstrate a grasp of statistical methodologies within business contexts, interpreting descriptive statistics, probability distributions, and sampling techniques, along with explaining principles underlying hypothesis testing and statistical inference. K3 (APPLY) CO 3: Implement statistical techniques to analyze real-world datasets, encompassing measures of central tendency, variability, and hypothesis tests, utilizing statistical software for computations and inference generation. K4 (ANALYZE) CO 4: Assess data through diverse statistical methods, exploring measures of shape, association, and hypothesis testing, facilitating informed decision-making and critical evaluation of statistical procedures. K5 (EVALUATE) CO 5: Judge the reliability and validity of statistical analyses, appraising sampling methods and hypothesis test accuracy, while weighing the strengths and limitations of statistical techniques for interpreting research findings. K6 (CREATE) CO 6: Employ statistical principles in experimental design and variance analysis, crafting research inquiries, selecting variables, and interpreting results, alongside generating predictive models like simple and multiple regressions using theoretical insights and software tools.

Subject Name: Data Analysis using Spreadsheet (DAS)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Describe Excel components, perform basic operations, and understand key features for effective spreadsheet management. K2 (UNDERSTAND) CO 2: Identify common Excel formulas, demonstrate chart formatting, and recognize PivotTables' significance in data analysis. K3 (APPLY) CO 3: Utilize Excel functions like VLOOKUP and COUNTIF, and apply modeling techniques for financial analysis. K4 (ANALYZE) CO 4: Analyze data with Excel's statistical tools, evaluate model accuracy, and determine optimal data presentation methods. K5 (EVALUATE) CO 5: Assess Excel's effectiveness in solving financial problems, and critically evaluate models and forecasts. K6 (CREATE) CO 6: Develop advanced spreadsheets with formulas and macros, design dynamic financial models, and generate customized reports for effective communication.

Subject Name: Tableau For Business Analytics (TBA)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Define Tableau's basic features, chart types, and functionalities for data visualization, understanding its role in representing data. K2 (UNDERSTAND) CO 2: Express data exploration, storytelling principles in Tableau, and demonstrate comprehension of the Crisp-DM framework for data analysis. K3 (APPLY) CO 3: Utilize Tableau for data manipulation, visualization, and storytelling to extract insights, applying techniques for engaging data narratives. K4 (ANALYZE) CO 4: Analyze data visualization requirements, selecting appropriate Tableau techniques, and evaluating their effectiveness in conveying insights. K5 (EVALUATE) CO 5: Critically assess Tableau visualizations for clarity, accuracy, and communication effectiveness, while evaluating its strengths and limitations in diverse business contexts. K6 (CREATE) CO 6: Design advanced Tableau visualizations to tackle specific business challenges, generating hypotheses from data analysis and translating insights into actionable strategies.

Subject Name: Marketing Management (MM)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Identify key components of marketing management, such as market segmentation, product life cycle, and pricing strategies. K2 (UNDERSTAND) CO 2: Comprehend the significance of marketing concepts within diverse business environments, including marketing information systems. K3 (APPLY) CO 3: Implement marketing strategies effectively in real-world scenarios using marketing information systems. K4 (ANALYZE) CO 4: Investigate consumer and business purchasing behavior to identify trends and implications. K5 (EVALUATE) CO 5: Assess the effectiveness of segmentation, targeting, and positioning strategies, and critique product life-cycle marketing methods. K6 (CREATE) CO 6: Develop innovative marketing strategies tailored to specific market segments and craft integrated communication plans.

Subject Name: Behavioural Sciences and Human Resource Management (BS & HRM)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Identify key OB concepts, theories, and their historical evolution, recognizing their relevance in diverse organizational contexts. K2 (UNDERSTAND) CO 2: Explain the significance of OB, interpreting how perception and work-related attitudes influence behavior, while summarizing the core elements of individual and group dynamics. K3 (APPLY) CO 3: Apply principles of group dynamics to enhance team performance, adeptly implementing HR planning and recruitment strategies, and utilizing diverse training methods for effective employee development. K4 (ANALYZE) CO 4: Analyze group dynamics to identify areas of synergy and dysfunction, examine the interconnections between motivation and other OB processes, and break down components of compensation systems. K5 (EVALUATE) CO 5:Assess HR strategy effectiveness across varied organizational settings, critically evaluate different training methods' potential to enhance employee performance, and evaluate and address motivational challenges within organizations. K6 (CREATE) CO 6: Devise a comprehensive resource management strategy to cultivate high-performance teams, craft customized compensation strategies aligned with organizational objectives, and generate innovative proposals integrating motivation theories.

Subject Name: Corporate Finance (CF)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Outline fundamental financial management concepts, such as the components of the financial system, basics of valuation, and principles of time value of money. K2 (UNDERSTAND) CO 2: Demonstrate comprehension of financial management principles, including the significance of financial management in business, the relationship between risk and return, and the impact of financing decisions on capital structure and valuation. K3 (APPLY) CO 3: Utilize financial management concepts in practical scenarios, including analyzing financial data, assessing different funding sources, calculating cost of capital, and employing capital budgeting techniques for investment decisions. K4 (ANALYZE) CO 4: Evaluate financial information to assess company performance, conduct financial statement analysis, and critically analyze capital structure theories regarding firm value maximization. K5 (EVALUATE) CO 5: Assess financial strategies and decisions, including the impact of financing options on cost of capital and capital structure, evaluating investment proposals, and examining the effectiveness of working capital management policies. K6 (CREATE) CO 6: Synthesize financial management concepts to develop comprehensive financial plans, design optimal capital structures, and construct investment portfolios tailored to meet specific financial objectives, considering risk tolerance and market conditions.

Subject Name: Data Analysis using SPSS (DA_SPSS)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Recall SPSS features, data import steps, and manipulation commands for effective data handling. K2 (UNDERSTAND) CO 2: Classify Grasp measurement scales, interpret descriptive statistics, understand hypothesis testing logic, and differentiate analysis techniques in SPSS. K3 (APPLY) CO 3: Apply data manipulation, descriptive statistics, and hypothesis testing techniques effectively in SPSS. K4 (ANALYZE) CO 4: analyze hypothesis test outcomes, evaluate assumptions, and extract insights from various analysis techniques in SPSS. K5 (EVALUATE) CO 5: Assess hypothesis test outcomes, validity of factor analysis, model fit, and method strengths/limitations in SPSS. K6 (CREATE) CO 6: Develop SPSS syntax, visually represent data, design research studies, and construct factor/structural equation models for advanced analysis and insight generation.

Subject Name: Business Research & Analytics (BRA)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Identify various types research methodologies and components of research problems and hypotheses. K2 (UNDERSTAND) CO 2: Explain research processes and understand research designs and associated errors. K3 (APPLY) CO 3: Apply research design knowledge to choose methodologies and employ data collection methods effectively. K4 (ANALYZE) CO 4: Analyze measurement scales and evaluate questionnaire designs for suitability in research. K5 (EVALUATE) CO 5: Assess data analysis techniques and critique research reports for structure and clarity. K6 (CREATE) CO 6: Develop research proposals and craft well-structured reports with actionable recommendations.

Subject Name: Employment Enhancement Skills (EES)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Identify and enumerate the key components and formats of essential placement documents, including resumes, cover letters, and job application emails/letters. K2 (UNDERSTAND) CO 2: Articulate the purpose and distinctions among various types of placement documents and their specific roles in the job application process. K3 (APPLY) CO 3: Create and customize placement documents such as resumes, cover letters, and job application emails/letters based on job descriptions and industry standards. K4 (ANALYZE) CO 4: Examine job descriptions to identify key skills and qualifications, and adjust placement documents accordingly. K5 (EVALUATE) CO 5: Evaluate the effectiveness and professionalism of placement documents and interview performance using established evaluation criteria. K6 (CREATE) CO 6: Develop comprehensive placement portfolios that include resumes, cover letters, and other relevant documents, incorporating advanced elements like video resumes and LinkedIn profiles.

Subject Name: Fundamentals of Machine Learning (FML)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Recognize foundational supervised learning concepts and methods, including regression, classification, model evaluation, and advanced topics like time series analysis and clustering. K2 (UNDERSTAND) CO 2: Identify principles behind various supervised learning techniques such as linear regression, logistic regression, decision trees, and ensembles, and identify appropriate applications for each. K3 (APPLY) CO 3: Implement linear regression, logistic regression, decision trees, and ensemble methods on datasets to make predictions and solve real-world problems. K4 (ANALYZE) CO 4: Evaluate supervised learning model performance using relevant metrics, and compare different model selection and optimization techniques to understand their impact on performance. K5 (EVALUATE) CO 5: Assess the effectiveness of supervised learning approaches in solving specific prediction tasks, considering model complexity, interpretability, and performance metrics. K6 (CREATE) CO 6: Develop advanced supervised learning models, such as support vector machines, neural networks, and gradient boosting, for complex prediction tasks, and innovate solutions through feature engineering and novel algorithmic approaches.

Subject Name: Supply Chain And Logistics Analytics (SC & LA)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Identify the fundamental concepts and terminology in Supply Chain Analytics, including key issues and the role of operations management within supply chains. K2 (UNDERSTAND) CO 2: Describe the significance of supply chain analytics in managing the flows of materials, money, information, and ownership, highlighting how these elements enhance the overall efficiency and effectiveness of a supply chain. K3 (APPLY) CO 3: Utilize forecasting and planning techniques to generate precise demand forecasts and develop effective inventory plans that optimize procurement and logistics operations in a supply chain. K4 (ANALYZE) CO 4: Examine supply chain networks using analytical tools and techniques to assess network planning and design logistics networks through heuristics or optimization methods, taking into account the roles of 3PL and 4PL logistics providers. K5 (EVALUATE) CO 5: Assess various supply chain strategies and analytics methods to determine their strengths and weaknesses, identifying the most effective approaches for specific supply chain challenges and scenarios. K6 (CREATE) CO 6: Develop innovative solutions for complex supply chain issues by integrating operations management principles with advanced supply chain analytics techniques, with a focus on network planning, procurement optimization, and logistics analytics.

Subject Name: Marketing, Web and Social Media Analytics (MW & SMA)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Recall and recognize fundamental concepts and techniques related to market segmentation and analytics. K2 (UNDERSTAND) CO 2: Demonstrate comprehension of the underlying principles and significance behind target segment selection and customer growth tracking. K3 (APPLY) CO 3: Utilize various segmentation techniques and analytics tools to solve real-world marketing challenges effectively. K4 (ANALYZE) CO 4: Evaluate and interpret campaign performance data using web analytics, social media metrics, and sentiment analysis. K5 (EVALUATE) CO 5: Critically assess the effectiveness of segmentation strategies, analytics tools, and campaign performance metrics. K6 (CREATE) CO 6: Synthesize insights from analytics to design innovative marketing strategies, customer acquisition plans, and market mix models.

Subject Name: HR Analytics (HRA)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Recall and recognize key HR analytics concepts and statistical methods, like indicators, metrics, and regression analysis. K2 (UNDERSTAND) CO 2: Comprehend the significance of HR analytics in decision-making, explain the role of workforce analytics in talent management, and interpret statistical analysis outcomes in HR contexts. K3 (APPLY) CO 3: Apply statistical methods and HR analytics tools effectively to analyze data, forecast workforce needs, and implement performance management techniques. K4 (ANALYZE) CO 4: Analyze HR data to identify trends and correlations guiding strategic decisions, evaluate retention analytics approaches, and assess compensation models for informed decision-making. K5 (EVALUATE) CO 5: Judge the effectiveness of HR analytics in addressing organizational challenges, assess the reliability of HR metrics, and evaluate ethical implications of HR data usage. K6 (CREATE) CO 6: Design HR analytics frameworks tailored to organizational needs, develop comprehensive workforce planning strategies, and innovate solutions to HR challenges using advanced analytics techniques.

Subject Name: Financial Analysis & Reporting (FAR)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Recall fundamental finance and accounting concepts, including definitions, types of companies, and the components of financial statements. K2 (UNDERSTAND) CO 2: Comprehend financial statement analysis techniques by explaining assessment methods and comparing company performances against industry benchmarks. K3 (APPLY) CO 3: Apply financial analysis through ratios to interpret company finances, including liquidity and leverage assessments. K4 (ANALYZE) CO 4: Analyze accounting quality and profitability drivers, utilizing techniques like CAMEL analysis to understand historical patterns. K5 (EVALUATE) CO 5: Evaluate prospective and credit analysis techniques, utilizing models like MDA and PCA to predict financial distress. K6 (CREATE) CO 6: Create comprehensive evaluations in mergers, acquisitions, and equity analysis, using various valuation methods to assess market value and risk.

Subject Name: Fraud And Risk Analytics (FRA)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Describe fundamental concepts and terminology, as well as key principles of classification models in fraud prevention and credit risk analysis. K2 (UNDERSTAND) CO 2: Infer methodologies in fraud analytics, credit risk analysis, and the significance of regulatory requirements. K3 (APPLY) CO 3: Apply classification models for fraud prevention and utilize regulatory analytics techniques for compliance in real-world scenarios. K4 (ANALYZE) CO 4: Analyze the effectiveness of fraud prevention techniques, models, and assess credit risk using advanced analytical tools. K5 (EVALUATE) CO 5: Evaluate the performance and ethical implications of fraud detection methods and credit risk assessment strategies. K6 (CREATE) CO 6: Design customized fraud prevention strategies and construct tailored probability of default (PD) models integrating insights from data analysis and regulatory compliance.

Subject Name: Summer Internship Programme 6 to 8 Weeks after First MBA-I (SIP)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Recall foundational MBA theories and concepts applicable to their industry during SIP and grasp organizational basics. K2 (UNDERSTAND) CO 2: Comprehend SIP project objectives, scope, and rationale within organizational and industry contexts; explain methodologies used. K3 (APPLY) CO 3: Utilize MBA knowledge to address real-world organizational challenges in SIP; employ appropriate research methods for data analysis. K4 (ANALYZE) CO 4: Evaluate organizational structures and strategies, identifying strengths, weaknesses, and proposing actionable recommendations from SIP findings. K5 (EVALUATE) CO 5: Assess effectiveness of SIP methodologies in meeting objectives and analyze its impact on the organization for improvement and future research. K6 (CREATE) CO 6: Develop comprehensive SIP reports communicating project details and innovative solutions, drawing insights from real-world organizational challenges.

Subject Name: Special Study Report (SSR)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Recall previously learned information and materials, including tools and techniques from the MBA course, and gathering relevant literature for the chosen topic or industry. K2 (UNDERSTAND) CO 2: Comprehend underlying theories and concepts relevant to their study area, as well as to summarize findings from literature reviews, understanding their implications for the industry under investigation. K3 (APPLY) CO 3: Apply learned tools and techniques to analyze the chosen industry or topic, along with the application of research methods to collect and analyze data specific to the study area. K4 (ANALYZE) CO 4: Identify trends and patterns within collected data, as well as to critically assess various viewpoints presented in the literature, integrating them into a coherent analysis. K5 (EVALUATE) CO 5: Assess the reliability of derived findings and the strength of employed methodologies, along with critiquing the strengths and weaknesses of the research methods utilized in the study. K6 (CREATE) CO 6: Construct a comprehensive study report following provided guidelines, as well as to generate innovative recommendations based on study findings, showcasing originality and creativity in their approach.

Subject Name: On-site Project Training / On Job Training 4 to 5 Months (Long Term) Dissertation Project Report (DPR)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Recall essential concepts and techniques for conducting industry or organizational studies. K2 (UNDERSTAND) CO 2: Interpret macro and micro-level industry or organizational issues through data and literature. K3 (APPLY) CO 3: Employ research methodologies and tools to gather and analyze primary and secondary data. K4 (ANALYZE) CO 4: Examine and differentiate management practices, theories, and structures within the industry or organization. K5 (EVALUATE) CO 5: Evaluate analysis findings and make evidence-based recommendations for improvements. K6 (CREATE) CO 6: Construct a comprehensive research proposal and report integrating all study components.

Subject Name: Multivariate Statistical Analysis (MSA)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Define key concepts and terminologies related to multiple linear regression, principal components analysis, exploratory factor analysis, multidimensional scaling, cluster analysis, canonical correlation, analysis of variance, multiple discriminant analysis, and structural equation modeling. K2 (UNDERSTAND) CO 2: Explain the fundamental principles and assumptions underlying multiple linear regression, principal components analysis, exploratory factor analysis, and other multivariate techniques. K3 (APPLY) CO 3: Utilize multiple linear regression and principal components analysis to analyze real-world datasets, identifying patterns and relationships among variables. K4 (ANALYZE) CO 4: Examine the outcomes of various multivariate techniques, such as ANOVA, MANOVA, MANCOVA, and cluster analysis, to derive meaningful conclusions and insights. K5 (EVALUATE) CO 5: Assess the suitability and effectiveness of different statistical models and methods, including canonical correlation analysis and multiple discriminant analysis, for addressing specific research questions. K6 (CREATE) CO 6: Design new models and frameworks by integrating techniques like confirmatory factor analysis and structural equation modeling to solve complex research problems.

Subject Name: Python For Business Analytics (PBA)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: List fundamental Python constructs, including data types, variables, and control structures, and describe the purpose and use of common Python libraries for data science. K2 (UNDERSTAND) CO 2: Summarize the concepts of lists, dictionaries, tuples, and sets, as well as loops and conditional statements, and explain how they are used to manage and manipulate data. K3 (APPLY) CO 3: Write Python functions and use libraries such as Numpy, Pandas, and Scipy to perform data analysis and manipulation tasks, demonstrating practical use of these tools. K4 (ANALYZE) CO 4: Analyze datasets by performing operations like filtering, grouping, and aggregating data using Pandas, and create visualizations using libraries like Matplotlib and Seaborn to interpret and present the data findings. K5 (EVALUATE) CO 5: Examine various code implementations, comparing their performance and suitability for different tasks, and select the most appropriate solution based on criteria such as speed, readability, and scalability. K6 (CREATE) CO 6: Design and implement end-to-end projects that involve data collection, extraction, cleaning, and analysis, culminating in meaningful insights and visualizations.

Subject Name: Foundation of Data Management in R (FDM)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Outline the fundamental aspects of the R ecosystem, including its inception, installation procedures, and key components like R packages and CRAN. K2 (UNDERSTAND) CO 2: Distinguish between the concepts of data types and measurement levels within R, and understand the principles of tidy data and basic data transformations. K3 (APPLY) CO 3: Implement loops, conditional expressions, and advanced techniques like PCA for image outlier detection and MDS for data analysis using R. K4 (ANALYZE) CO 4: Employ exploratory data analysis techniques, including descriptive statistics, correlation analysis, and ANOVA, and interpret various data visualizations using ggplot2. K5 (EVALUATE) CO 5: Assess the appropriateness of statistical tests for different data types and critically evaluate data transformation and cleaning techniques in R. K6 (CREATE) CO 6: Generate new variables, perform complex data transformations, and derive insights from diverse data types such as time-series and spatial data using R.

Subject Name: Contemporary issues in Business Analytics (CIBA)

Statements: Course Outcomes: After completing the course student will be able to: BLOOM’S TAXANOMY COURSE OUTCOMES K1 (REMEMBER) CO 1: Identify and recall key contemporary issues and trends in various domains of business analytics. K2 (UNDERSTAND) CO 2: Explain the relevance and implications of contemporary issues in business decision-making and strategy formulation. K3 (APPLY) CO 3: Use appropriate business analytics tools and techniques to analyze real-world data related to contemporary issues. K4 (ANALYZE) CO 4: evaluate literature and existing research to identify gaps and opportunities related to contemporary issues. K5 (EVALUATE) CO 5: Assess the effectiveness of different business analytics strategies and solutions in addressing contemporary issues. K6 (CREATE) CO 6: Develop and present a comprehensive report and presentation on a selected contemporary issue, proposing innovative solutions and future research directions.

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2022-2023 MBA in Business Intelligence Syllabus

Gujarat University

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