Robin Garcia

Implementation of BI solutions for operational steering

- Analysis of business needs and definition of steering indicators (KPI) for several departments.

- Design and maintenance of Power BI reporting solutions used for operational and decision-making steering.

- Design and optimization of analytical models (star schema, fact/dimension tables) to structure steering data.

- Formalization and standardization of business indicator calculation rules.

- Exploitation and structuring of data from orchestrated flows (business SQL views) feeding analytical models and decision-making reports.

- Optimization of model and query performance.

- Deployment of analytical models through industrialized deployment processes (Git + CI/CD pipeline).

- Collaboration with data engineering teams for the industrialization and reliability of data flows.

Power BI Service – BI Distribution Platform

- Analysis of Power BI Service potential as a centralized report distribution platform.

- Study of BI governance mechanisms (shared datasets, workspaces, security and access management).

- Reflection on the evolution of the existing BI architecture towards cloud and more industrialized models.

Exploration of a modern data architecture around Microsoft Fabric (outside client context)

- Implementation of a complete analytical chain: data ingestion via REST API and transformation via Dataflows.

- Data storage and structuring in a Lakehouse.

- Creation of a Power BI semantic model for analytical exploitation.

- Orchestration of processing via pipelines to automate data and report refresh.

- Design of complex SQL marketing targets for CRM campaigns (SMS, email, telemarketing).

- Analysis of marketing campaign performance (A/B testing, control groups, impact measurement).

- Analysis of customer behaviors (segmentation, consumption, churn).

- Definition and monitoring of loyalty, retention, and sales performance indicators.

- Production of analyses and decision-making reporting for marketing and CRM teams.

- Contribution to data projects: propensity scoring, cleaning and structuring of customer databases.

- Identification and analysis of anomalies or inconsistencies in customer data in conjunction with technical teams.

- Collaboration with IT departments for the provision and reliability of data used in analyses and targeting.

- Implementation of prospect targeting and dispatch of SMS, Email, Mail, and Telemarketing campaigns.

- Contribution to the automation of recurring marketing campaigns.

- Monitoring and improvement of the prospect database.

- Participation in marketing scoring projects in collaboration with the data team.