2022 SAG Award Winners


Project Goal

This study is one of the exemplary studies on the interactive use of Geographic Information Systems
and Machine Learning. It is an artificial intelligence study carried out in order to determine the fiber
investment areas of telecommunication companies and to predict the rate of return to sales by
years. In this study, a total of 80 data categories and the XGBoost algorithm were used in machine
learning, location-based advanced analysis methods were used and a study was carried out in
harmony with the Machine Learning workflow.
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Business Problem Solved

For two decades, Turkcell—like many telecommunications providers throughout the world—had a practice of assessing customer demand. However, Turkcell was looking to be more surgical in understanding where customer demand is expected to come from over the next 10 years. Large volumes of socioeconomic and infrastructure data were available, but there was the question of how to bring all this information together into machine learning models that would help Turkcell sales staff members know how to accurately mobilize and prioritize their sales activities.

Technology Implemented

To meet the needs of the business and improve capabilities, the Turkcell team leveraged ArcGIS technology, including ArcGIS Pro, ArcGIS ModelBuilder, and machine learning to develop the web app GEDI. Creating this application consisted of integrating over 80 individual categories of data.

Development Team Biography

Gülnur Özbas - Senior Expert Geodata Scientist
Experienced Geographic Information Systems Analyst with a demonstrated history of working in the telecom industry. Skilled in ArcGIS, QGis, Databases, Big Data Analytics, SQL, Pyhton. Strong information technology professional with a Bachelor's Degree focused in Urban Planning from Istanbul Technical University.
Burak Gülseren - Strategic Planning Engineer
Currently strategic planning engineer at Turkcell also working on fiber planning and feasibilities of big and small projects.
Additionally working on Machine Learning , Deep Learning and Data Analyzing algorithms and related projects by using python.
Saygin Isik - Principal Strategic Planning Engineer
Experienced Access Engineer with a demonstrated history of working in the telecommunications industry. Competence on Fiber Network Design and strong Implementation/Realization experience, hands on experience in GIS, Data, System Analysis and Machine Learning Projects.