mehdi feki

Prepared the data by applying K-means clustering in Python to group countries that have the same behavior and PCA for model dimensionality, resulting in a 25% improvement in data processing efficiency and 100% accurate handling of missing values. Implemented statistical models such as ARIMA in Python to predict the number of subscribers of fixed technologies like ADSL Designed an interactive dashboard with Power Bi to visualize IPv4 allocations for each Orange Country and the different IPv4 data.

Loaded the Data Warehouse by running the ETL process with Talend to process the banking transaction data and on the daily Logs to support error detection and analysis for SOAP services. Identified crucial KPIs for evaluating business performance and visualizing them in dashboards with Power BI that effectively facilitate data-driven decision making. Trained by Keyrus France on Talend ESB. Technologies used: Talend, SSIS, PowerBi SQLServer, Python

Collaborated with a team of 6 members to define the objectives and KPIs required for the project. Developed detailed dimensional data models to structure data efficiently. Loaded the Data Warehouse by running the ETL process with Talend on the data . Developed of Machine Learning and Data Mining algorithms in Python to predict driver performance. Created an interactive dashboard to visualize all previous data with Power Bi. Technologies used: PowerBi, Talend, PostgreSQL, Machine Learning