Academic Blueprint & Exam Guide
MBA IN CLOUD ERP — 3RD SEMESTER DETAILED SYLLABUS
Curriculum reference for EIILM / Raiganj University students. Prepare across core modules, research methodology, enterprise financial flows, and people analytics.
Schedule 1-on-1 Exam Tutoring & Mentorship →Semester III Overview
The Third Semester of the MBA in Cloud ERP bridges quantitative decision-making, core cloud financial architectures (R2R, P2P, O2C), talent planning analytics, and master data governance. Review the full subject outlines below to organize your studies and project preparations.
301
Research Methodology
- Unit I: Basic Concepts in Research Methodology: Meaning, objectives, and types of research methods; criteria for sound scientific inquiry; framing hypotheses and operationalizing variables.
- Unit II: Planning and Designing Research: Research design frameworks; exploratory, descriptive, and causal designs; research design selection criteria.
- Unit III: Sampling Design, Distributions & Scaling: Sampling design steps; probability vs. non-probability sampling (random, stratified, cluster, multi-stage, multi-phase, quota); sampling error, sample distribution of mean and proportion, sample size estimation; scaling methods (Likert, Thurstone, arbitrary, and factor scales).
- Unit IV: Methods of Data Collection: Primary data collection using questionnaires and schedules; secondary data sources; relative merits of collection techniques.
- Unit V: Data Processing: Data editing, coding, entry; frequency distributions, stem-and-leaf displays, histograms, cross-tabulations, and data transformation.
- Unit VI: Data Analysis & Statistical Modeling: Parametric and non-parametric hypothesis testing; multiple regression, logistic regression, R-square interpretation, multicollinearity, autocorrelation; time series decomposition (additive/multiplicative); trend analysis (least squares, exponential smoothing); business modeling in MS Excel.
- Unit IX: Report Writing & Presentation: Structural layout of business and technical reports, executive presentation techniques, and documentation formats.
303
Cloud ERP for Financial Transformation
- Unit I: Cloud ERP in FP&A: Foundational concepts; strategic benefits for FP&A; differences between legacy on-premise systems and cloud ERP; aligning modern FP&A functions with corporate strategy; core cloud transaction cycles (R2R, P2P, O2C).
- Unit II: Cloud ERP Architecture, Data & Governance: SaaS, PaaS, IaaS service models; multi-tenant vs. single-tenant architectures; Master Data Management (MDM); data governance, auditability, compliance, and legacy migration frameworks.
- Unit III: Financial Planning, Budgeting & Forecasting in Cloud: Collaborative cloud planning; automated budgeting workflows; rolling forecasts; scenario planning and driver-based forecasting; BI integration, spreadsheet plugins, version control, and approval hierarchies.
- Unit IV: Management Reporting & Embedded Analytics: KPI scorecard design; statutory and regulatory compliance reporting; profitability modeling, cost-to-serve analysis; real-time vs. periodic reporting; AI/ML-driven anomaly detection.
- Unit V: Consolidation, Cash & Working Capital Management: Intercompany eliminations and consolidated ledgers; cash management; liquidity forecasting; treasury operations; automated cash flow analytics.
- Unit VI: Implementation, Change Management & Trends: Governance for finance transformation; ecosystem apps; modern trends (robotic process automation, augmented analytics, AI forecasting); ROI measurement and benefits realization.
Prescribed Reference: Davenport, T. H. — Analytics at Work.
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304
Financial Planning and Analytics with Cloud ERP
- Unit I: Strategic Drivers of Finance Transformation: Cloud ERP architecture; on-premise vs. cloud trade-offs; drivers of digital financial modernization; executing R2R, P2P, and O2C in unified cloud environments.
- Unit II: Cloud Architecture, Data & Security: Cloud service models; tenancy architectures; enterprise data models and master data governance; identity management, audit trails, and data migration planning.
- Unit III: Financial Modules & Process Automation: General ledger, AP, AR, fixed assets, cash management; project accounting; automated revenue recognition; third-party ERP integrations.
- Unit IV: Implementation Strategy & Process Redesign: Enterprise transformation roadmaps; business process mapping; data cleansing strategies; stakeholder alignment and QA controls.
- Unit V: Embedded Analytics & Cloud Planning: Executive dashboards; statutory compliance frameworks; KPI architecture; predictive intelligence using machine learning.
- Unit VI: Close Optimization & Case Studies: Period-end financial close optimization; Robotic Process Automation (RPA); app extensions; major SaaS ERP ecosystems; post-implementation ROI evaluation.
Prescribed Reference: Monk, E., & Wagner, B. — Concepts in Enterprise Resource Planning.
305
HR Analytics and Workforce Planning with Cloud ERP
- Unit I: Introduction to Data-Driven Human Resources: Analytics in modern talent management; cloud ERP as an enterprise HR enabler; aligning people strategy with business KPIs; core HR workflows in cloud environments.
- Unit II: HR Data Governance & Architecture: Integrating core HRIS, payroll, time, talent acquisition, and performance data; data hygiene; master data management; data privacy, security, and compliance.
- Unit III: Workforce Planning & Predictive Modeling: Descriptive, diagnostic, predictive HR modeling; dynamic headcount forecasting; supply vs. demand modeling; attrition analytics; skills gap identification.
- Unit IV: Total Rewards, Performance & DE&I Metrics: Compensation benchmarking; succession pipelines; learning analytics; diversity, equity, and inclusion (DE&I) metrics; talent mobility models.
- Unit V: Change Management & Cloud Enablement: Governance for cloud HR implementations; data stewardship; user adoption programs; security and access management.
- Unit VI: Advanced Analytics & Future Trends: Machine learning models in human resources; ethical considerations and algorithmic bias; HR transformation case studies; workforce analytics maturity roadmaps.
306
Data Governance and Analytics in Cloud ERP
- Unit I: Foundations of Enterprise Data Governance: Governance vs. data management; data quality dimensions (accuracy, completeness, timeliness, validity); managing master, reference, and transactional data; data stewardship roles.
- Unit II: Data Architecture & Metadata: Canonical ERP models across customer, vendor, material, and financial domains; metadata and data lineage analysis; SAP S/4HANA Cloud and Oracle ERP Cloud integration patterns.
- Unit III: Data Quality & Cleansing Techniques: Cleansing customer, supplier, and GL accounts; data hygiene dashboards and automated monitoring in cloud ERP platforms.
- Unit IV: Analytics Enablement: Embedded ERP reporting vs. external enterprise data warehouses; analytics workflows across finance, sales, and supply chains; data readiness frameworks.
- Unit V: Data Security, Privacy & Regulatory Compliance: RBAC and ABAC access controls; data masking and encryption (in transit and at rest); regulatory compliance (GDPR, DPDP).
- Unit VI: Program Design & Adoption Maturity: Governance operating models, council escalation hierarchies; change management frameworks; measuring data maturity using enterprise KPIs.
Prescribed References:
1. Ladley, J. — Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program.
2. Kimball, R., & Ross, M. — The Data Warehouse Toolkit.
3. Redman, T. C. — Data Quality: The Implications for Data Governance and Analytics.
1. Ladley, J. — Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program.
2. Kimball, R., & Ross, M. — The Data Warehouse Toolkit.
3. Redman, T. C. — Data Quality: The Implications for Data Governance and Analytics.
Academic & Corporate Mentorship
Amrita Jha
Management Educator & Softskills Trainer Since 2010 | Founder, PSB Training Academy
Preparing for postgraduate examinations while mastering modern ERP tools requires structured execution. Connect directly with our academy to access curated study plans, one-on-one subject coaching, and corporate readiness training designed to turn syllabus topics into placement results.