| Abstract [eng] |
Nowadays, one of the main tasks that businesses have is to select an advanced analytical platform which would have all required tools, methods and algorithms to carry on wanted analysis. The goal of the thesis is to overview the most advanced analytical tools and to evaluate their functionality while using retail sales data analysis. One of the thesis tasks is to choose and overview the tools that are being used in analytics. Based on Garner`s company rating there were three analytical platforms selected as being the best. Clustering analysis and time series where applied using selected analytical platforms IBM, SAS, KNIME. K – means method was used for clustering analysis and RFM (Recency, Frequency, Monetary) model was used with different analytical tools which helped finding meaningful client groups. The second part of analysis was focused on time series analysis, where sales sum forecasting to the future was done using ARIMA model. The functionality of different analytical tools was evaluated based on analysis where speed, methods, algorithms, estimations and statistics variety of different tools was estimated. Based on analysis done on the retail sales data SAS was selected as the best analytical tool. |
