{"title":"Big Data: Sources and Best Practices for Analytics","authors":"A. Luntovskyy, L. Globa","doi":"10.1109/UkrMiCo47782.2019.9165334","DOIUrl":null,"url":null,"abstract":"Cyber-PHY, IoT, sensor networks, Robotics (thick and server-less mobile applications), real-time network applications (thin clouds clients) can generate large arrays of unmanaged, weakly structured, and non-configured data of various types, known as \"Big Data\". With the acceleration of industrial development \"Industry 4.0\" processing of such data became considerably more complicated. However, so-called problem \"Big Data\" is hard to solve or resist nowadays! The paper discusses the Best Practises and Case Studies aimed to overcoming of the Big Data problematics.","PeriodicalId":6754,"journal":{"name":"2019 International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo)","volume":"30 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UkrMiCo47782.2019.9165334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Cyber-PHY, IoT, sensor networks, Robotics (thick and server-less mobile applications), real-time network applications (thin clouds clients) can generate large arrays of unmanaged, weakly structured, and non-configured data of various types, known as "Big Data". With the acceleration of industrial development "Industry 4.0" processing of such data became considerably more complicated. However, so-called problem "Big Data" is hard to solve or resist nowadays! The paper discusses the Best Practises and Case Studies aimed to overcoming of the Big Data problematics.
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