MSc in Business Data Analysis & Decision Management
Explore this MSc programme at FINCOM Paris, a business school in Paris connecting analytical skills with business decisions.
Programme overview
Design analytical systems, evaluate competitive intelligence and support organisational decisions. Compare predictive models, evidence and implementation outcomes through cases in finance, insurance, industry, telecommunications and healthcare.
FINCOM Paris — Paris College of Commerce and Financial Management. Duration: 2 years. Programme reference: ESPAST-28-M.
Building on relevant undergraduate study, the programme develops comparison of methods, work with complex constraints and independent research or applied project management.
Study pathways
Business analytics; market and competitive intelligence; operational decisions. Pathways share a common core. Applicants indicate their preferred pathway; availability is confirmed before admission.
Learning outcomes
- Apply analytical architecture to requirements, data and governance, documenting methods, evidence and the basis for professional judgement.
- Apply advanced models to prediction, validation and interpretation, documenting methods, evidence and the basis for professional judgement.
- Apply competitive intelligence to multi-source analysis and uncertainty, documenting methods, evidence and the basis for professional judgement.
- Apply operational optimisation to constraints, resources and scenarios, documenting methods, evidence and the basis for professional judgement.
- Apply organisational decisions to stakeholders and implementation, documenting methods, evidence and the basis for professional judgement.
- Apply analytical review to reproducibility, ethics and outcomes, documenting methods, evidence and the basis for professional judgement.
Learning content and competency modules
| Module | Learning content | Assessment evidence |
|---|---|---|
| Analytical architecture | Requirements, data and governance. Advanced research and complex project analysis. | Problem definition and analytical report |
| Advanced models | Prediction, validation and interpretation. Advanced research and complex project analysis. | Reproducible case or model file |
| Competitive intelligence | Multi-source analysis and uncertainty. Advanced research and complex project analysis. | Data and operational records with quality checks |
| Operational optimisation | Constraints, resources and scenarios. Advanced research and complex project analysis. | Option comparison and testing evidence |
| Organisational decisions | Stakeholders and implementation. Advanced research and complex project analysis. | Project plan and collaboration records |
| Analytical review | Reproducibility, ethics and outcomes. Advanced research and complex project analysis. | Final report and oral defence |
Study progression
- Year 1: deepen analytical architecture, advanced models, competitive intelligence; undertake literature or case research and define the project question and approach.
- Year 2: integrate operational optimisation, organisational decisions, analytical review through an independent research or applied project, final report and oral defence.
Projects and practice
Investigate an organisational decision problem, design an analytical system and evaluate implementation outcomes and risks.
Project submissions document the problem, process, individual contribution, validation evidence and limitations. Individual contributions are assessed within team projects. Placements and external projects depend on actual arrangements; no particular employer or placement is guaranteed.
Teaching and assessment
Business cases, data laboratories, scenario analysis and team projects use public, simulated or authorised information. Cases may draw on finance, insurance, industry, telecommunications and healthcare.
Module assignments, cases, practical work, staged projects and the final oral defence assess conceptual accuracy, methods, evidence quality, reliability, communication and reflection. Weightings, reassessment and extension rules are published before teaching begins. Moodle can support resources, assignments, quizzes and feedback; practical activities are recorded and assessed separately.
Entry requirements
Provide evidence of a relevant undergraduate qualification or equivalent experience in business, management, economics, finance, data or a related field. Explain your statistical, analytical and organisational background. Technical investigation pathways also assess networking and data skills.
Submit education evidence, transcripts, a CV, a motivation statement and any required project portfolio. Teaching languages, language evidence and translation requirements are specified in the intake announcement. Website language options do not determine teaching language.
Diploma
Complete the required modules, assessments, final project and applicable academic requirements to receive an institution-issued diploma.
Career development
Business data analyst; decision analyst; business intelligence project manager. Employment depends on skills, experience and employer requirements; regulated roles also require applicable qualifications and authorisations. Further study is subject to the receiving institution’s admission requirements.
Tuition and fees
Contact admissions for the tuition and payment terms applicable to your chosen programme before enrolment.
Applications
Select this programme and study level when submitting a preliminary application. The admissions office reviews materials and contacts the applicant. A preliminary application is not an admission decision or a payment commitment.
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