THE APPLICATION OF BIG DATA TECHNOLOGY IN THE ANALYSIS OF COMMERCIAL CIRCULATION DATA IN EMERGING INDUSTRIES.
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| Title: | THE APPLICATION OF BIG DATA TECHNOLOGY IN THE ANALYSIS OF COMMERCIAL CIRCULATION DATA IN EMERGING INDUSTRIES. |
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| Authors: | XIAOQIN JIA1 xiaoqinjiareans1@outlook.com, LI ZHANG1 |
| Source: | Scalable Computing: Practice & Experience. Nov2024, Vol. 25 Issue 6, p5486-5493. 8p. |
| Subjects: | Commercial statistics, Emerging industries, Digital technology, Deep learning, Data analytics, Big data |
| Abstract: | Inside the generation of rapid technological development, rising industries are increasingly counting on big facts to pressure growth and innovation. This examine explores the transformative effect of huge facts generation on the analysis of commercial circulate statistics in those burgeoning sectors. By way of harnessing numerous and voluminous datasets, organisations inside rising industries can uncover crucial insights, optimise delivery chains, are expecting marketplace developments, and enhance patron reviews. The paper begins by using outlining the unique challenges and possibilities that emerging industries face within the virtual landscape, emphasising the want for strong facts-driven techniques. We delve into the methodologies of large facts analytics, together with data acquisition, garage, processing, and visualization strategies tailor-made for the nuanced requirements of these industries. A crucial examination of case research wherein huge facts has been efficaciously carried out offers realistic insights into its effectiveness and barriers. The examine similarly investigates the role of advanced analytics, system studying, and AI in refining data evaluation techniques, providing a complete view of the way those technologies synergistically make contributions to strategic selection-making. Moral issues, especially regarding records of privateness and safety, are also addressed, acknowledging the responsibilities that accompany the utilization of huge information. The paper concludes by projecting future traits in big statistics programs within rising industries, which includes the capacity for predictive analytics and the integration of IoT gadgets. This research now not only underscores the significance of big statistics in revolutionising business flow however also serves as a guiding framework for industry leaders and stakeholders trying to navigate the complexities of the digital age in rising markets. [ABSTRACT FROM AUTHOR] |
| Copyright of Scalable Computing: Practice & Experience is the property of Scalable Computing: Practice & Experience and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 180063334 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: THE APPLICATION OF BIG DATA TECHNOLOGY IN THE ANALYSIS OF COMMERCIAL CIRCULATION DATA IN EMERGING INDUSTRIES. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22XIAOQIN+JIA%22">XIAOQIN JIA</searchLink><relatesTo>1</relatesTo><i> xiaoqinjiareans1@outlook.com</i><br /><searchLink fieldCode="AR" term="%22LI+ZHANG%22">LI ZHANG</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Scalable+Computing%3A+Practice+%26+Experience%22">Scalable Computing: Practice & Experience</searchLink>. Nov2024, Vol. 25 Issue 6, p5486-5493. 8p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Commercial+statistics%22">Commercial statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Emerging+industries%22">Emerging industries</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+technology%22">Digital technology</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analytics%22">Data analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Big+data%22">Big data</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Inside the generation of rapid technological development, rising industries are increasingly counting on big facts to pressure growth and innovation. This examine explores the transformative effect of huge facts generation on the analysis of commercial circulate statistics in those burgeoning sectors. By way of harnessing numerous and voluminous datasets, organisations inside rising industries can uncover crucial insights, optimise delivery chains, are expecting marketplace developments, and enhance patron reviews. The paper begins by using outlining the unique challenges and possibilities that emerging industries face within the virtual landscape, emphasising the want for strong facts-driven techniques. We delve into the methodologies of large facts analytics, together with data acquisition, garage, processing, and visualization strategies tailor-made for the nuanced requirements of these industries. A crucial examination of case research wherein huge facts has been efficaciously carried out offers realistic insights into its effectiveness and barriers. The examine similarly investigates the role of advanced analytics, system studying, and AI in refining data evaluation techniques, providing a complete view of the way those technologies synergistically make contributions to strategic selection-making. Moral issues, especially regarding records of privateness and safety, are also addressed, acknowledging the responsibilities that accompany the utilization of huge information. The paper concludes by projecting future traits in big statistics programs within rising industries, which includes the capacity for predictive analytics and the integration of IoT gadgets. This research now not only underscores the significance of big statistics in revolutionising business flow however also serves as a guiding framework for industry leaders and stakeholders trying to navigate the complexities of the digital age in rising markets. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Scalable Computing: Practice & Experience is the property of Scalable Computing: Practice & Experience and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.12694/scpe.v25i6.3342 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 5486 Subjects: – SubjectFull: Commercial statistics Type: general – SubjectFull: Emerging industries Type: general – SubjectFull: Digital technology Type: general – SubjectFull: Deep learning Type: general – SubjectFull: Data analytics Type: general – SubjectFull: Big data Type: general Titles: – TitleFull: THE APPLICATION OF BIG DATA TECHNOLOGY IN THE ANALYSIS OF COMMERCIAL CIRCULATION DATA IN EMERGING INDUSTRIES. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: XIAOQIN JIA – PersonEntity: Name: NameFull: LI ZHANG IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 18951767 Numbering: – Type: volume Value: 25 – Type: issue Value: 6 Titles: – TitleFull: Scalable Computing: Practice & Experience Type: main |
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