Data analysis and visualisation supported by artificial intelligence
| dc.contributor.advisor | Harangi, Balázs | |
| dc.contributor.author | Shamel, Kamila | |
| dc.contributor.department | DE--Informatikai Kar | |
| dc.date.accessioned | 2026-07-14T16:41:48Z | |
| dc.date.available | 2026-07-14T16:41:48Z | |
| dc.date.created | 2026-04-28 | |
| dc.description.abstract | In this thesis, I examine how artificial intelligence can improve data analysis and visualization, especially in e-commerce. I go through a full workflow that includes steps such as data cleaning, machine learning modeling, and building interactive dashboards to help businesses make decisions. One of the main things I did was use a Random Forest model for sales forecasting and customer segmentation using RFM analysis, and then show all that in a Power BI dashboard. My work shows that AI can help us go beyond just describing data and actually predict and find useful insights. But there are some limits, like the fact that I used fake data and only had a short time period. In general, I think this thesis provides a hands-on, organized approach to building AI-powered data systems. | |
| dc.description.course | Gazdaságinformatikus | |
| dc.description.degree | BSc/BA | |
| dc.format.extent | 53 | |
| dc.identifier.uri | https://hdl.handle.net/2437/413220 | |
| dc.language.iso | en | |
| dc.rights.info | Hozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében. | |
| dc.subject | PowerBI | |
| dc.subject | Visualization | |
| dc.subject | Data analysis | |
| dc.subject.dspace | Informatics | |
| dc.title | Data analysis and visualisation supported by artificial intelligence | |
| dc.title.subtitle | thesis | |
| dc.title.translated | Mesterséges intelligencia által támogatott adatelemzés és vizualizáció |
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