Beata is a senior economic analyst at Central Bank of Hungary. She has a degree in applied mathematics. She worked for almost 20 years as methodological adviser of the Hungarian Central Statistical Office and than in2024 joined the team of Digitalisation Technology Department at the Central Bank of Hungary. She has many experiencies on data analysis, econometric and time series modeling.

The Central Bank of Hungary

Processing and modeling Online Cash Register data using machine learning methods

Online cash registers (OCR) have become a widespread tool in retail since their gradual introduction in 2013 in Hungary. The analysis and modeling of the data derived from them can play a crucial role in supporting important national economic decisions. The presentation explores the main processing and modeling steps that we performed in case of product name categorization, time series analysis and time series modeling with statistical and deep learning methods.