FBA Hosts Analytics Week event

In line with keeping pace with the rapid developments in digital transformation and artificial intelligence, the Department of Information Technology and Management Systems at the Faculty of Business Administration, Al Maaref University, organized a week of training workshops in analytics for its students. The week concluded on Friday, December 19, 2025, at the university campus (Building C) in Beirut, aiming to equip participants with essential knowledge and practical skills to understand data and transform it into strategic decisions across various business environments.

The week featured a series of training workshops in analytics and data science for students and concluded on Friday, December 19, 2025, at the university campus in Beirut (Building C). The initiative aimed to equip participants with essential knowledge, practical tools, and core skills needed to understand, analyze, and transform data into strategic decisions across various business environments.

A select group of faculty members and field specialists delivered the workshops over five days. The instructors included Dr. Kassem Danach, Head of the MIT Department; Dr. Ali Hammoud; Mr. Rabih Tarraf; Dr. Mohammad Msheik; Mr. Hasan Rammal; Dr. Rayan Al-Sibae; Dr. Hussein Hazimeh; and Mr. Mostafa Muzahem.

The program covered a range of advanced topics, most notably machine learning fundamentals, with a simplified explanation of the differences between supervised and unsupervised learning. In addition, an applied session titled Advanced Excel Analytics focused on moving beyond traditional spreadsheets toward extracting strategic insights that support informed decision-making.

The workshops also addressed the conceptual dimension of analytics through the analysis of Key Performance Indicators (KPIs) within Business Intelligence, highlighting their role in performance measurement and in linking data to organizational objectives. This was complemented by a specialized session on analytics automation using the n8n platform, aimed at simplifying processes and enhancing operational efficiency.