Daniel Moutou

Creation of a data model in the cloud data warehouse (snowflake)

Creation of a semantic model in Power BI for strategic decision-making on Toyota Motor Europe's insurance products

Context:

Société Générale Group wants to leverage the power of Public Cloud and use its data to develop high-value use cases. In this context, I was able to lead 3 projects in parallel in my role as Data Analyst:

1. Monetize data through Power BI and help accelerate Public Cloud use cases

2. Manage the implementation of the Power BI service offering and lead studies on Analytics solutions

3. Analyze data to optimize the retail bank's customer strategy

Missions:

• Extract, combine data sources, create, industrialize, and maintain business or customer-oriented dashboards (monitoring data quality statistics and associated operational risks, net promoter score, customer complaints)

• Define controls to verify compliance with defined rules and monitor key performance indicators

• Optimize commercial strategy and customer experience by analyzing feedback from middle/back-office agents, CRM activity data, and satisfaction metrics.

• Accelerate the use of Analytics solutions within the Group while respecting associated security requirements and those of local and European regulators.

• Identify existing internal Analytics platforms and onboard users to the Power BI offering, its benefits, and best practices (managing two consultants)

• Analyze needs and use cases for intelligent document processing (OCR machine learning, LLM) to improve business process efficiency.

Results:

• 26% improvement in retail banking customer satisfaction compared to 2022

• Deployment of several dashboards on Power BI Service fed by ETL pipelines

• Implementation of the Group-wide Power BI service offering

Team: 1 DE, 2 DS, 1 BA, 1 DA, 1 Lead

Stakeholders: IT, Lead Managers, Management Control, Customer Service

Context:

The France entity of the World Standardization Organization wishes to increase its subscriber base by launching a new initiative focused on accelerating E-Commerce. The objectives are therefore to:

1. Identify the reasons for customer churn and reduce the attrition rate

2. Open new promising sectors to attract new subscribers

Missions:

• Orient the new strategy based on data (feedback from sales managers, sector data, CRM, attrition reports)

• Compile internal (CRM, financial) and external data sources available in compliance with GDPR using Power BI, to identify prospects in different sectors and determine the need to create new ones.

• Synthesize data and derive personas (sector composition, temporal evolution, products sold, subscriber profile and behavior, use of the online barcode creation tool) to evaluate the effectiveness of the current strategy.

• Assist in the deployment of a machine learning algorithm for attrition prediction and propose tailored loyalty solutions for different profiles.

Results:

• Opening of two new sectors in response to personas identified by the Power BI data model (view of subscriber and prospect behavior)

• Automation of the monthly analysis of subscriber/unsubscriber base movements for management control via a Python script