Publication:
Managing and Optimizing Big Data Workloads for On-Demand User Centric Reports

dc.contributor.authorBaicoianu, Alexandra
dc.contributor.authorScheianu, Ion Valentin
dc.date.accessioned2025-09-03T12:50:36Z
dc.date.issued2023
dc.description.abstractThe term “big data” refers to the vast amount of structured and unstructured data generated by businesses, organizations, and individuals on a daily basis. The rapid growth of big data has led to the development of new technologies and techniques for storing, processing, and analyzing these data in order to extract valuable information. This study examines some of these technologies, compares their pros and cons, and provides solutions for handling specific types of reporting using big data tools. In addition, this paper discusses some of the challenges associated with big data and suggests approaches that could be used to manage and analyze these data. The findings demonstrate the benefits of efficiently managing the datasets and choosing the appropriate tools, as well as the efficiency of the proposed solution with hands-on examples.
dc.identifier.citationBaicoianu, A.; Scheianu, I.V. Managing and Optimizing Big Data Workloads for On-Demand User Centric Reports. Big Data Cogn. Comput. 2023, 7, 78. https://doi.org/10.3390/bdcc7020078
dc.identifier.urihttps://repository.unitbv.ro/handle/123456789/403
dc.language.isoen
dc.publisherBig Data Cogn. Comput.
dc.subjectbig data
dc.subjectoptimization
dc.subjectperformance
dc.subjectDruid
dc.subjectterabyte
dc.subjectdata skewness
dc.subjectunbalanced dataset
dc.subjectHadoop
dc.subjectMapReduce
dc.subjectSpark
dc.titleManaging and Optimizing Big Data Workloads for On-Demand User Centric Reports
dc.typeArticle
dspace.entity.typePublication

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