Mohamed-Ali Ksouri

As part of a cross-functional team at SNCF headquarters, I participated in a strategic project to consolidate data from various group entities (Stations & Connections, Network, Travelers, Keolis, Geodis), aiming to improve the management and communication of Key Performance Indicators (KPIs) within the five subsidiaries comprising the parent company. Missions performed: Complete modeling of a data warehouse from ERP (Oracle) extractions of accounting data, ensuring data aggregation and cross-OLAP analysis for a balance sheet, as well as query optimization and compliance with previously validated data formats. Design of a BI architecture with Power BI: cleaning of large datasets (+ 1.5 million rows per table, i.e., a FACT table of 20 million rows), management of relationships between tables, application of the snowflake model. Creation of DAX measures to code 17 KPIs called accounting management rules (example: personnel costs, capitalized production, inter-company revenue, etc.) previously defined in the specifications. Use of M language for custom querying and transformations on PowerQuery. Advanced development of dynamic dashboards and automated reports, enabling the analysis and visualization of these financial and operational indicators across the group's 5 entities. Use of SQL for data extraction, transformation, and loading, from Oracle IT sources for each company (Stations & Connections, SNCF Travelers, Network, etc.). Use of Excel VLOOKUPs to verify the integrity of over 3000 rows of dimensional tables for accounting data classification. Regular collaboration with business teams (finance, management control, IT) to ensure consistency between delivered tools and operational/decision-making needs.

As part of a financial unit within a consulting firm, I participated in a project analyzing investments and economic indicators. Missions performed:

Transformation and consolidation of data in an SQL database using bulk insert and update scripts, processing over 30,000 records from online databases (Worldometer, INS, etc.).

Design of a data warehouse fed by automated ETL flows with SSIS from heterogeneous sources (CSV, PDF, web pages).

Development of interactive dashboards in Power BI for at least 7 key financial indicators (GDP, investment rate, consumer price index, etc.) using a star schema and DAX measures.

Development of a predictive algorithm in Python to forecast economic trends such as GDP for 2024, using the XGBoost Machine Learning algorithm.

During this learning experience in Business Intelligence, I received guidance from my tutor to apply the fundamental concepts learned in coursework within an industrial poultry farming context. Mission performed:

Cleaning and manipulation of data related to Poulina's poultry production sites using Excel with basic functions such as CONCATENATE, TRIM, LEN, TEXT, etc. Deployment of dashboards from pivot tables.

SQL querying, ETL operations, and data staging on Talend, data visualization, and storytelling on Power BI to rank production sites by efficiency.