dc.creatorNaeem, Muhammad Zaid
dc.creatorJamal, Tauseef
dc.creatorDíaz-Martínez, Jorge L
dc.creatorButt, Shariq Aziz
dc.creatorMontesano, Nicolò
dc.creatorTariq, Muhammad Imran
dc.creatorDe-La-Hoz-Franco, Emiro
dc.creatorDe-La-Hoz-Valdiris, Ethel
dc.date2022-07-07T14:07:19Z
dc.date2022-07-07T14:07:19Z
dc.date2021-11-26
dc.date.accessioned2023-10-03T19:32:43Z
dc.date.available2023-10-03T19:32:43Z
dc.identifierNaeem, M. et al. (2022). Trends and Future Perspective Challenges in Big Data. In: Pan, JS., Balas, V.E., Chen, CM. (eds) Advances in Intelligent Data Analysis and Applications. Smart Innovation, Systems and Technologies, vol 253. Springer, Singapore. https://doi.org/10.1007/978-981-16-5036-9_30
dc.identifier978-981-16-5035-2
dc.identifierhttps://hdl.handle.net/11323/9346
dc.identifierhttps://doi.org/10.1007/978-981-16-5036-9_30
dc.identifier10.1007/978-981-16-5036-9_30
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier978-981-16-5036-9
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9170571
dc.descriptionWe are living in an era of big data, where the process of generating data is continuously been taking place with each coming second. Data that is more varied and extremely complex in structure (unstructured/semi-structured) with problems of indexing, sorting, searching, analyzing and visualizing are major challenges of today’s organizations. Big data is always defined by its 5-v characteristics which are Volume, Velocity, Veracity, Variety, and Value. Almost each data model comprising big data is dependent on these 5-v characteristics. A large number of researches have been done on velocity and volume, but the complete and efficient solution for the variety is still not available in the markets. Traditional solutions provided by DBMS generally use multidimensional data type. However, many new data types cannot be compatible with these traditional systems. Big Data is a general problem affecting different fields, whether it is business, economic, social security or scientific research. To analyze huge data sets in order to get insights and find patterns in data is called big data analytics. Big data analytics is the need of every corporate and state of the art organization to look forward and make useful decisions. This paper comprises of discussion on current issues, opportunities, trends, and challenges of big data aimed to discuss variety in more detail. An efficient solution for the big data variety problem will be discussed.
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languageeng
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.publisherGermany
dc.relationAdvances in Intelligent Data Analysis and Applications;
dc.relationSmart Innovation, Systems and Technologies
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dc.rightsAtribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
dc.rights© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rightshttp://purl.org/coar/access_right/c_14cb
dc.sourcehttps://link.springer.com/chapter/10.1007/978-981-16-5036-9_30
dc.subjectBig data
dc.subjectBig data challenges
dc.subjectBig data approaches
dc.titleTrends and future perspective challenges in big data
dc.typeCapítulo - Parte de Libro
dc.typehttp://purl.org/coar/resource_type/c_3248
dc.typeText
dc.typeinfo:eu-repo/semantics/bookPart
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/redcol/resource_type/CAP_LIB
dc.typeinfo:eu-repo/semantics/draft
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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