Big Data with Cloud Computing: Discussions and Challenges

被引：82
|
作者：
Sandhu, Amanpreet Kaur [1 ]
机构：
[1] Chandigarh Univ, Univ Inst Comp, Mohali 140413, India
来源：
BIG DATA MINING AND ANALYTICS | 2022年 / 5卷 / 01期
关键词：
big data; data analysis; cloud computing; Hadoop; OF-THE-ART; TECHNOLOGIES; ALGORITHMS; HADOOP;
D O I：
10.26599/BDMA.2021.9020016
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With the recent advancements in computer technologies, the amount of data available is increasing day by day. However, excessive amounts of data create great challenges for users. Meanwhile, cloud computing services provide a powerful environment to store large volumes of data. They eliminate various requirements, such as dedicated space and maintenance of expensive computer hardware and software. Handling big data is a time-consuming task that requires large computational clusters to ensure successful data storage and processing. In this work, the definition, classification, and characteristics of big data are discussed, along with various cloud services, such as Microsoft Azure, Google Cloud, Amazon Web Services, International Business Machine cloud, Hortonworks, and MapR. A comparative analysis of various cloud-based big data frameworks is also performed. Various research challenges are defined in terms of distributed database storage, data security, heterogeneity, and data visualization.
引用
收藏
页码：32 / 40
页数：9
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