Arthur Sowe

CABD: entity created less than 6 months ago. Mission - analyze the group's e-business data and propose concrete improvement areas to the 39 regional offices.

• Analysis of e-business data (leads, conversion rates, journeys) via MicroStrategy and Metabase, SQL queries on group databases - to identify performance levers and formulate concrete recommendations for the 39 offices.

• Distribution Models POC: weekly monitoring over 8 weeks via MicroStrategy and SQL - comparison of conversion rates by distribution model to identify the most effective at the group level.

• Management of Digital Marketing campaigns via Metabase and MicroStrategy - measurement of the ROI of each marketing action to demonstrate the value brought by CABD to the Crédit Agricole group.

• Collaboration with Business Owners of the 5 universes (insurance, consumer credit, savings, housing, banking) - analysis of digital journey conversion KPIs via MicroStrategy to guide product decisions.

• Production of monthly e-business reports via MicroStrategy and SQL - synthesis of performance by office to feed action plans of animation managers and disseminate best leads practices.

• CABD recognized as the e-business data reference by the 39 offices in less than 6 months of existence - thanks to regular, reliable, and actionable analyses.

• Optimal distribution model identified over 8 weeks of analysis; actionable recommendations provided to group management for large-scale deployment.

Analysis mission of industrial data with high operational stakes during the grape harvest period, within the LVMH Industrial IT Department. Central role of processing sensor data (IoT) to transform raw signals into decision-making indicators, anticipate quality risks, and equip field teams in real-time process control of fermentation.

• Collection, cleaning, and analysis of critical data from IoT sensors (time, temperature, CO₂): structuring raw data streams into reliable and usable indicators for operational teams.

• Design and deployment of real-time dashboards (Power BI / GCP BigQuery) for continuous monitoring of fermentation indicators, with predictive modeling of CO₂ peaks allowing proactive anticipation of quality risks.

• Implementation of an automatic alert system based on business thresholds defined with quality experts, to trigger corrective actions in real-time and ensure data traceability throughout the process.

• Significant reduction in operational and quality risks thanks to early detection of fermentation anomalies, in a context of high time pressure (harvest).

• Measurable gain in decision-making time for field teams: shift from reactive to predictive management, with increased confidence in data thanks to reliable and centralized indicators.

Mission carried out within the Groupama Nord-Est Regional Office, in a context of profound modernization of the group: community-based data actions around a common group DWH, standardization of management tools (COGNOS to Qlik Sense migration), and harmonization of indicators between offices.

Central role in supporting this data transformation - driving adoption of new tools, aligning business practices with group standards, and leveraging data as a lever for operational and strategic management within the office.

• Construction and prioritization of the data product roadmap according to business OKRs and expected value by management.

• Backlog management, user story writing, sprint facilitation with data engineers and BI teams.

• Definition and validation of strategic KPIs - construction of a shared data dictionary across 6 departments.

• Facilitation of product governance bodies (steering committees, scoping workshops, sprint reviews).

• Change management: training, data awareness workshops, educational materials for business teams.

• Successful COGNOS → Qlik Sense migration - rapid adoption across all departments thanks to structured change management.

• Harmonization of indicators between 6 departments - faster decisions and reduced interpretation conflicts.

• Significant improvement in business confidence in data and decision-making reports.