Freelancer profile translated to English.

Description

Data Analyst - Power BI | DAX | Excel | SQL

Is your data asource of anxiety: slow reports, unreliable figures, or a lack of strategic visibility?

**Unreliable data is costly**, both in time and missed opportunities.

I act as a Data Analyst Consultant Power BI | DAX | Excel | SQL to transform this anxiety into a stable competitive advantage.

For 3 years, I have been assisting VSEs, SMEs, and large corporations with datacentralization**, **migrationto Fabric, and reporting **automation**.

My achievements:

-> Mon Chasseur Immo**: Management of the **BI overhaul and migration to Microsoft Fabric(Lakehouse). Centralization of 100% of business rules and consolidation of **+10 data sources**, ensuring the reliability and maintainability of the architecture.

**-> Fyrebrain**: Design of **strategic Power BI dashboards**, optimizing customer behavior understanding and segmentation.

-> Compétences & Développement**: Development of data **enrichmentPython scripts (web scraping) to meet France Compétences compliance thresholds.

My approach is turnkey: I deliver astable, documented, and scalableBI solution (Fabric / Power BI), ensuring data reliability at the source and full autonomy for your teams for sustainable analysis.

Technical Stack:Power BI, Microsoft Fabric, DAX, Power Query, Python, SQL.

Would you like to secure the reliability of your data and transform your manual reporting into rapid strategic management?

Contact me:I offer a quick chatto discuss your challenges and define a concrete approach.

Response guaranteed within 24 hours.

Industry field of expertise

Languages

French
Native or bilingual
English
Conversational

Workplace preferences

Can work on-site

Montpellier (up to 50km), Toulouse (up to 50km), Paris (up to 50km), Lyon (up to 50km), Montpellier (up to 50km)

MON CHASSEUR IMMO
Data analyst
REAL ESTATE
September 2023 - September 2025 (2 years)
Montpellier, France
→ Mission Objective:Complete modernization of the company's BI stackandmigration to Microsoft Fabricto improve datareliability and strategic value(CRM, Marketing, HR), ensuring accelerated reporting and fact-based decision-making.

→ Achievements:

*Managed the complete migrationof the BI architecture toMicrosoft Fabric(Lakehouse).

*BI Auditfor data reliability at the source and identification of strategic KPIs.
Development ofSpark Notebooks (PySpark, Scala)and ETL/ELT processes (Python/SQL) for ingestion/storage.
Design ofstrategic Power BI dashboards(Advanced DAX) for Marketing, HR, and Management teams.
*Support and trainingfor business users on new BI tools.
Key Results: Centralized data in Fabric, increased reliability, **significant reduction in reporting time, better KPI visibility**, and easier team adoption.

→ Technical Stack: Power BI, Microsoft Fabric, Python, Pandas, Scala, Spark, Excel/CSV, REST API

→ Data Sources: Hubspot, SQLServer, PennyLane, Brevo, Sharepoint, Livestrorm, Recruitee, SurveySparrow, Windsor, Yousign
Microsoft Power BI Microsoft Fabric ETL (Extract, Transform, Load) Process SQL Python
Compétences et Développement
Freelance Data Analyst Mission – LinkedIn Data Scraping & Exploitation
EDUCATION AND E-LEARNING
September 2025 - October 2025 (1 month)
Montpellier, France
→ Mission Objective: Ensure thecomplianceof professional integration indicators for France Compétences files byimproving and enriching the databasethrough web scraping and data analysis techniques.

→ Achievements:

*Development of a dedicated Python scriptfor targetedscrapingand collection of former students' professional LinkedIn profiles.

*Cleaning, structuring, and standardizationof collected data (deduplication, format normalization, title standardization).
Impact: Significant enrichment of the database and **drastic reduction in missing data rates**.
Delivery of areliable and structuredfinal file (CSV/Excel) for integration analysis.
Key Results:Immediate improvement in the reliabilityof produced statistics and indicators transmitted to steering committees for decision-making, andsaving several weeksof manual scraping.

→ Technical Stack: Power BI, Excel, Python, Pandas, Excel/CSV, REST API, Apify, FantomBuster

→ Data Sources: Excel/csv, Linkedin
ETL Python Web Scraping Microsoft Excel Reporting