veribilim

Veribilim, a Turkish term that combines “veri” (data) and “bilim” (science), refers to the academic and applied discipline of extracting knowledge and insights from data. It encompasses statistical analysis, machine learning, data mining, and a range of computational techniques used to understand patterns, make predictions, and support decision‑making. The field emerged in the early 21st century as the volume, variety, and velocity of digital information grew beyond the capacity of traditional statistics and database management.

The core methodology of veribilim involves identifying a problem, collecting and cleaning data, selecting appropriate models, training and validating those models, interpreting results, and communicating findings. This process is iterative: insights often lead to new questions and more data collection. Veribilim draws heavily on mathematics, computer science, and domain expertise, making it inherently interdisciplinary. In Turkey, veribilim has been integrated into university curricula, research institutes, and industry sectors such as finance, health care, and public administration through both academic programs and professional training.

Practical applications include predicting economic indicators, diagnosing medical conditions from imaging, optimizing logistics networks, and personalizing digital marketing. Veribilim also intersects with ethics, privacy, and governance, prompting guidelines that address bias, transparency, and accountability in data‑driven systems. As global data continue to expand, veribilim plays a pivotal role in harnessing this resource for societal benefit, and its frameworks are increasingly adopted in international research collaborations, demonstrating its growing influence outside Turkey.