About Elodie
French
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English
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German
Basic
Experience
- VianeoSenior Data AnalystSOFTWARE PUBLISHINGSeptember 2022 - July 2025 (2 years and 10 months)Valbonne, Franceđ MISSIONComplete refactoring of the data architecture and implementation of the analytical strategy to support the growth of the member area.đȘ WHAT I DID1. Refactoring of the "Projects" databaseâ Management of a Graph legacyâ Data optimization (snowflake architecture)2. Building Apache Superset dashboardsâ Extreme SQL optimization to meet Superset dataset <1min constraintâ Business needs gathering + optimized visualizationsâ Support for the business team3. DESIGN OF A MODERN & SCALABLE DATA ARCHITECTUREâ Extraction from 30 MariaDB databases â MariaDB Data Warehouseâ Transformation with dbt (transformations, documentation, automated tests)â DigDash data cubes with GDPR/multi-client managementâ Cross-client aggregation for enterprise dashboardsđ MEASURABLE RESULTSâ Performance: Queries going from 2+ minutes to <1 minuteâ Scalability: Architecture capable of supporting 10x growthâ Governance: Multi-client GDPR system, complete audit trailsâ Documentation: dbt auto-generates transformation documentationâ Quality: Automated tests on data uniqueness, data freshnessđ ïž TECHNOLOGIES USED- Advanced SQL (constants, indexing, partitioning)- Apache Superset (performant dashboards, BI)- dbt (data transformation, documentation, tests)- MariaDB (design, optimization, DWH)- DigDash (data cubes, visualizations)- GDPR/Governance (multi-tenancy, audit)đŻ IMPACTImplementation of a modern data architecture that allows Vianeo to:- Serve its clients with reliable and performant data- Scale the infrastructure without refactoring- Automatically document and test transformations- Comply with GDPR governanceNote: Deployment stopped before completion due to economic context.
- SUPRALOGIT Product Owner / Data AnalystSOFTWARE PUBLISHINGJune 2020 - June 2022 (2 years)Antibes, Provence-Alpes-CĂŽte dâAzur, FranceCREATION OF THE "MEMBER AREA" DATABASEđŻ THE CHALLENGESupralog needed a database to:- Manage members and their data- Support vacation rental bookings- Manage inventory and stock- Migrate from a legacy systemComplexity: Multiple data types, many business stakeholders, no room for error.đĄ MY SOLUTIONPhase 1: UNDERSTANDING NEEDS- Detailed interviews with the business- Documentation of existing workflows- Identification of hidden needs- Writing complete functional specificationsPhase 2: DATABASE DESIGN- Data modeling (members, bookings, inventory)- Schema design (tables, relationships, constraints)- Migration plan from the old system (data import)- Architecture for future scalabilityPhase 3: IMPLEMENTATION & MIGRATION- Creation of the production database- Data injection (strict validation)- Exhaustive testing (data quality)- Training for the business teamPhase 4: SUPPORT & MAINTENANCE- Analysis and resolution of data bugs- Regular updates- Data quality checks- Continuous support for the teamđ RESULTSâ Production-ready database at launchâ 0 critical errors after go-liveâ Business team autonomous in data managementâ System capable of supporting growthâ 100% adoption rate (satisfied team)đ ïž TECHNOLOGIESSQL | Database Design | Data Migration | Project ManagementđŒ KEY LEARNINGS1. Specifications are THE foundation (garbage in = garbage out)2. Project management is 50% of a data analyst's job3. Data injection = very important but often underestimated4. Business/technical communication = critical success factorđ IF YOU HAVE A SIMILAR NEED...Database construction, data migration, or post-launch support?Contact me to discuss.
- SUPRALOGIT Business Analyst for Air FranceAVIATION AND AEROSPACEJune 2018 - May 2020 (1 year and 11 months)Sophia AntipolisAIR FRANCE-KLM - JUSTIFYING THE VALUE OF A BACKEND TEAM THROUGH DATAđŻ THE CHALLENGEAir France-KLM had a classic problem:"Why invest in this backend team? What is the ROI?"The NBA (Next Best Action) project: API/Web service to personalize offersto customers. But was it really profitable? Was it worth maintaininga full team?đĄ MY SOLUTIONInstead of just saying "it's good," I quantified the impact:Phase 1: IN-DEPTH ANALYSIS- CTR & Conversion Rates of NBA offers- Sales projections "with NBA" vs "without NBA" (A/B testing)- Impact of new paid options on revenue- Temporal tracking of evolutionPhase 2: IMPACT MODELING- Estimation of additional sales generated by NBA- ROI of the backend team = revenue generated / team costs- Sensitivity analysis: "if we reduce the team, impact on revenue"Phase 3: MONTHLY REPORTING- Monthly report for management (SAFe level)- Real-time dashboards- Executive summary for decision makers- Tracking of key KPIsđ RESULTSâ Management convinced of the valueâ Result: The team received an additional developer to accelerate the addition of new optionsâ Monthly report requested cross-planeđŒ KEY LEARNINGS1. Data without storytelling = nothing. Narration is crucial.2. Well-thought-out hypotheses = powerful tools for justifying budgets3. Monthly reporting = creating an artifact that is consulted regularly = success4. In large organizations, understanding SAFe/Agile = facilitated communicationđ ïž TECHNOLOGIESA/B Testing Analysis | Python | Excel/PowerPoint | Hypothetical Modelingđ IF YOU HAVE A SIMILAR NEED...Justify team budgets? Create strategic reporting?Contact me to discuss.
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Education
- Engineering DegreePolytech Nice Sophia, Valbonne, FR2016Gestion des risques, hydrogéologie, gestion de projet, Python, SQL, macros VBA
- MSc EuroAquaeNewcastle University, Newcastle, UK2015Impacts du changement climatique sur les milieux cĂŽtiers, VBA, anticipation des crues et inondations, gestion de bassin versant
Certifications
- Project ManagementM2i Formation2021
- The Essentials of Power BILinkedIn2021