Understanding the Videogame Market with Data Analysis
| dc.contributor.advisor | Tomán, Henrietta | |
| dc.contributor.author | Nguyen Van Tri, Hung | |
| dc.contributor.department | DE--Informatikai Kar | |
| dc.date.accessioned | 2024-02-01T10:21:09Z | |
| dc.date.available | 2024-02-01T10:21:09Z | |
| dc.date.created | 2023-11-29 | |
| dc.description.abstract | The thesis aims to apply data science methods on data for the videogame industry. Thorough analysis on different aspects of the market will be made and predictive models will be built to forecast market trends and future sales. The final goal is to gain in-depth understanding of the videogame market and the projection of the industry in the near future. This thesis can prove useful to game developers and publishers in deciding on their next projects. Prediction of sales can give indication on how successful a particular product can be, so decisions can be made regarding different aspects (how much resource, what platform to release on, etc.). Investors may also make use of this thesis to predict up-and-coming businesses to make informed decisions | |
| dc.description.course | Gazdaságinformatikus | |
| dc.description.degree | BSc/BA | |
| dc.format.extent | 52 | |
| dc.identifier.uri | https://hdl.handle.net/2437/365840 | |
| dc.language.iso | en | |
| dc.rights.access | Hozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében. | |
| dc.subject | Data Science | |
| dc.subject | Machine Learning | |
| dc.subject | Data Analysis | |
| dc.subject.dspace | DEENK Témalista::Informatics::Information Technology | |
| dc.title | Understanding the Videogame Market with Data Analysis |
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