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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Noppon Wongta | en_US |
dc.contributor.author | Juggapong Natwichai | en_US |
dc.date.accessioned | 2022-10-16T07:08:43Z | - |
dc.date.available | 2022-10-16T07:08:43Z | - |
dc.date.issued | 2021-01-01 | en_US |
dc.identifier.issn | 23674520 | en_US |
dc.identifier.issn | 23674512 | en_US |
dc.identifier.other | 2-s2.0-85102071988 | en_US |
dc.identifier.other | 10.1007/978-3-030-70639-5_25 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85102071988&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/76361 | - |
dc.description.abstract | Data pipeline architecture in game is a system that captures, organizes, and routes data, which enables reporting or data analytics. Such results can be utilized by game developers. A main challenge is that to allow huge data from the game clients to flow to the system, while the core game processing must not be interrupted. This paper reviews thorough concepts related to the game analytics. In addition, the observations of the data pipeline components in games are made and discussed to evaluate the challenges which are real-time data pipeline and in-memory process implementation. | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.title | End-to-End Data Pipeline in Games for Real-Time Data Analytics | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Lecture Notes on Data Engineering and Communications Technologies | en_US |
article.volume | 65 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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