Luis Eder Velázquez Peña, Lisbeth Rodríguez Mazahua, G. A. Hernández, Beatriz Alejandra Olivares Zepahua, S. G. P. Camarena, Isaac Machorro Cano
{"title":"Big data visualization: Review of techniques and datasets","authors":"Luis Eder Velázquez Peña, Lisbeth Rodríguez Mazahua, G. A. Hernández, Beatriz Alejandra Olivares Zepahua, S. G. P. Camarena, Isaac Machorro Cano","doi":"10.1109/CIMPS.2017.8169944","DOIUrl":null,"url":null,"abstract":"In the last 20 years the term of Big Data took strength which refers to datasets that in size exceed the ability of typical database tools to capture store manage and analyze. Big Data visual analysis is a new field that is emerging as a powerful tool for extracting useful information. This paper discusses the revision of 83 articles on visualization techniques for Big Data of the last six years for the future realization of a comparative analysis of these techniques and to determine which are the most optimistic when analyzing Big Data.","PeriodicalId":265026,"journal":{"name":"2017 6th International Conference on Software Process Improvement (CIMPS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th International Conference on Software Process Improvement (CIMPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMPS.2017.8169944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In the last 20 years the term of Big Data took strength which refers to datasets that in size exceed the ability of typical database tools to capture store manage and analyze. Big Data visual analysis is a new field that is emerging as a powerful tool for extracting useful information. This paper discusses the revision of 83 articles on visualization techniques for Big Data of the last six years for the future realization of a comparative analysis of these techniques and to determine which are the most optimistic when analyzing Big Data.