Bachelor in Business Data Analysis & Decision Management
Explore this Bachelor programme at FINCOM Paris, a business school in Paris connecting analytical skills with business decisions.
Programme overview
Learn how business organisations, statistics and data management turn operational questions into analytical tasks. Market, customer and operations cases develop skills in lawful collection, data quality, visualisation and decision communication.
FINCOM Paris — Paris College of Commerce and Financial Management. Duration: 3 years. Programme reference: ESPAST-28-B.
The programme progresses from foundations and method exercises to staged projects, enabling students to define problems, select methods and explain findings.
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 business fundamentals to markets, organisations and processes, documenting methods, evidence and the basis for professional judgement.
- Apply data foundations to databases, cleaning and statistics, documenting methods, evidence and the basis for professional judgement.
- Apply indicator design to objectives, definitions and quality, documenting methods, evidence and the basis for professional judgement.
- Apply market intelligence to sources, competition and verification, documenting methods, evidence and the basis for professional judgement.
- Apply visual analytics to charts, interpretation and limitations, documenting methods, evidence and the basis for professional judgement.
- Apply decision practice to options, experiments and evaluation, documenting methods, evidence and the basis for professional judgement.
Learning content and competency modules
| Module | Learning content | Assessment evidence |
|---|---|---|
| Business fundamentals | Markets, organisations and processes. Guided exercises and applied cases. | Problem definition and analytical report |
| Data foundations | Databases, cleaning and statistics. Guided exercises and applied cases. | Reproducible case or model file |
| Indicator design | Objectives, definitions and quality. Guided exercises and applied cases. | Data and operational records with quality checks |
| Market intelligence | Sources, competition and verification. Guided exercises and applied cases. | Option comparison and testing evidence |
| Visual analytics | Charts, interpretation and limitations. Guided exercises and applied cases. | Project plan and collaboration records |
| Decision practice | Options, experiments and evaluation. Guided exercises and applied cases. | Final report and oral defence |
Study progression
- Year 1: build foundations in business fundamentals and data foundations, with guided cases, academic reading and communication.
- Year 2: develop indicator design and market intelligence through pathway projects and evaluation of methods and results.
- Year 3: integrate visual analytics and decision practice in a final project, documented portfolio and oral defence.
Projects and practice
Build a business analytics dashboard and decision briefing documenting indicators and evidence sources.
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 secondary education or equivalent study. A foundation in mathematics, logical reasoning and written communication is recommended. Business, data or social-research projects may support the application.
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 assistant; operations analysis assistant; market intelligence assistant. 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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