Big Data and Quality: A Literature Review

被引：0

作者：

Lakshen, Guma Abdulkhader ^{[1
]}

Vranes, Sanja ^{[2
]}

Janev, Valentina ^{[2
]}

机构：

[1] Univ Belgrade, Sch Elect Engn, Bul Kralja Aleksandra 73, Belgrade 11120, Serbia

[2] Mihailo Pupin Inst, Volgina 15, Belgrade 11060, Serbia

来源：

2016 24TH TELECOMMUNICATIONS FORUM (TELFOR) | 2016年

关键词：

Big Data; Quality assessment; stream processing; survey; Big Data frameworks;

D O I：

暂无

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

Big Data refers to data volumes in the range of Exabyte (1018) and beyond. Such volumes exceed the capacity of current on-line storage and processing systems. With characteristics like volume, velocity and variety big data throws challenges to the traditional IT establishments. Computer assisted innovation, real time data analytics, customer-centric business intelligence, industry wide decision making and transparency are possible advantages, to mention few, of Big Data. There are many issues with Big Data that warrant quality assessment methods. The issues are pertaining to storage and transport, management, and processing. This paper throws light into the present state of quality issues related to Big Data. It provides valuable insights that can be used to leverage Big Data science activities.

引用

页码：802 / 805

页数：4

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