A Comparative Perspective on Technologies of Big Data Value Chain
dc.authorid | AYDIN, AHMET ARIF/0000-0002-4124-7275 | |
dc.contributor.author | Aydin, Ahmet Arif | |
dc.date.accessioned | 2024-08-04T20:54:47Z | |
dc.date.available | 2024-08-04T20:54:47Z | |
dc.date.issued | 2023 | |
dc.department | İnönü Üniversitesi | en_US |
dc.description.abstract | Data is one of the most valuable assets in the digital era because it may conceal hidden valuable insights. Diverse organizations in diverse domains overcome the challenges of the big data value chain by employing a wide range of technologies to meet their needs and achieve a variety of goals to support their decision-making. Due to the significance of data-oriented technologies, this paper presents a model of the big data value chain based on technologies used in the acquisition, storage, and analysis of data. The following are the paper's contributions: First, a model of the big data value chain is developed to illustrate a comprehensive representation of the big data value chain that depicts the relationships between the characteristics of big data and the technologies associated with each category. Second, in contrast to previous research, this paper presents an overview of technologies for each category of the big data value chain. The third contribution of this paper is to assist researchers and developers of data-intensive systems in selecting the appropriate technology for their specific application development use cases by providing examples of applications and use cases from prominent papers in a variety of fields and by describing the capabilities and stages of the technologies being presented so that the right technology is used at the right time in the big data collection, processing, storage, and analytics tasks. | en_US |
dc.identifier.doi | 10.1109/ACCESS.2023.3323160 | |
dc.identifier.endpage | 112146 | en_US |
dc.identifier.issn | 2169-3536 | |
dc.identifier.scopus | 2-s2.0-85174850844 | en_US |
dc.identifier.scopusquality | Q1 | en_US |
dc.identifier.startpage | 112133 | en_US |
dc.identifier.uri | https://doi.org/10.1109/ACCESS.2023.3323160 | |
dc.identifier.uri | https://hdl.handle.net/11616/101635 | |
dc.identifier.volume | 11 | en_US |
dc.identifier.wos | WOS:001090513500001 | en_US |
dc.identifier.wosquality | Q2 | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.indekslendigikaynak | Scopus | en_US |
dc.language.iso | en | en_US |
dc.publisher | Ieee-Inst Electrical Electronics Engineers Inc | en_US |
dc.relation.ispartof | Ieee Access | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Analytics | en_US |
dc.subject | acquisition | en_US |
dc.subject | big data technologies | en_US |
dc.subject | information systems | en_US |
dc.subject | storage | en_US |
dc.title | A Comparative Perspective on Technologies of Big Data Value Chain | en_US |
dc.type | Article | en_US |