Rihem Torkhani

Data & Reporting Project – International Transport / Supply Chain

Development of ETL/ELT pipelines with Azure Data Factory for the integration and transformation of logistics data (ERP, Excel, SQL Server, carriers). Design of a decision-making architecture under Microsoft Fabric with data structuring in a Data Lake / Data Warehouse. Creation of interactive dashboards with Microsoft Power BI for Supply Chain KPI monitoring: shipments, delivery times, logistics costs, inventory, and import/export volumes. Data modeling, ETL flow optimization, and processing automation in an Azure Cloud environment. Technical environment:

Azure Data Factory, Microsoft Fabric, Power BI, SQL Server, T-SQL, ETL/ELT, Azure Cloud, GitHub, Azure DevOps.

Intelligent Platform for CRM Data Integration, Validation, and Quality Monitoring

Team: DATA Microsoft

CRM Data Integration & Processing: Design of ETL pipelines with SSIS for ingesting, cleaning, and transforming data from CSV files into Microsoft Dynamics 365. Automatic logging of technical errors with T-SQL packages. Machine Learning & Error Prediction (ML.NET): Training of supervised models with ML.NET to automatically detect errors in CRM entities. Development of a quality scoring system for data flows. Web Development – ASP.NET: Creation of a web platform for error prediction: intelligent upload, display of errors by cards, continuous integration, MVC architecture. Dashboarding & BI: Creation of dynamic dashboards with Power BI for CRM data quality monitoring and predictive reporting. Correction & Intelligence: Deployment of a correction system based on an LLM (Large Language Model) and a RAG (Retrieval-Augmented Generation) architecture, with automatic recommendations. Recommendation and History of Uploaded, corrected files with email notifications

CRM & Power Platform Environment: Design of data workflows in Dynamics 365, process automation via Power Platform (Dataverse, Power Automate). Database & Cloud: Use of SQL Server, flow orchestration with Airflow. Technical environment: Dynamics 365, Power Platforms, SSIS, ML.NET, ASP.NET Core, C#, SQL Server, T-SQL, Power BI, Airflow, GitHub, Azure DevOps, RAG, LLM, OpenAI API.

Development of a segmentation pipeline to Dynamics 365 Sales using Machine Learning techniques

Team: Technology & Service Delivery – Dynamics 365 Sales:

Data Science & Predictive Modeling

Development of a customer segmentation pipeline integrated with Dynamics 365 Sales, based on supervised learning techniques: KNN, Random Forest, Decision Trees, implemented with Scikit-learn (Python).

ETL & Data Processing

Extraction, transformation, and loading of data via SSIS (SQL Server Integration Services), preparation of CRM data for analytical processing.

Business Intelligence & Dashboarding

Creation of interactive reports with Power BI, highlighting customer segments and KPIs.

Database & Flow Management

Manipulation of SQL Server and MySQL databases for customer data analysis and storage, structuring datasets for ML training.

CRM Dynamics 365 & Power Platform

Design of data workflows for populating CRM entities, integration of customer segments into the Power Platform (Power Automate, Dataverse).

Integration & Deployment

Deployment of the segmentation model via Azure Machine Learning, integration into Dynamics 365 using Azure APIs & Connectors.

Project Management & Agile Collaboration

Work in Agile methodology, versioning and collaboration on GitHub, participation in sprint reviews and planning meetings.

Technical environment: Python, Scikit-learn, SQL Server, MySQL, SSIS, Power BI, Azure Machine Learning, Dynamics 365, Power Platforms, DataBricks, Spark.