Abstract
Today the challenge facing every company is the enormous quantity of data being captured, at yearly, monthly, weekly, daily and hourly levels and how this data may be used. Despite the amount of data often this data is limited regarding company processes and their analysis. This can be solved by preprocessing data, after its quality evaluation, for process mining activities. Prepared data can be used for data dimensions’ coverage and having dimension members filled financial analyst may analyze this data from different perspectives for discovery of certain patterns, anomalies and frauds. This paper presents primary results of data cube dimensions fill according data of real organizations General Ledger information. Provided examples help to illustrate the possibility cover majority dimension members and give material for further researches.
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Acknowledgments
This paper presents primary results of research project “Enterprise Financial Performance Data Analysis Tools Platform (AIFA)”. The research project is funded by European Regional Development Fund according to the 2014–2020 Operational Programme for the European Union Funds’ Investments under measure No. 01.2.1-LVPA-T-848 “Smart FDI”. Project no.: 01.2.1-LVPA-T-848-02-0004; Period of project implementation: 2020-06-01–2022-05-31.
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Lopata, A. et al. (2021). Financial Data Preprocessing Issues. In: Lopata, A., Gudonienė, D., Butkienė, R. (eds) Information and Software Technologies. ICIST 2021. Communications in Computer and Information Science, vol 1486. Springer, Cham. https://doi.org/10.1007/978-3-030-88304-1_5
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