Healthcare big data processing mechanisms: The role of cloud computing

2019 ◽  
Vol 49 ◽  
pp. 271-289 ◽  
Author(s):  
Lila Rajabion ◽  
Abdusalam Abdulla Shaltooki ◽  
Masoud Taghikhah ◽  
Amirhossein Ghasemi ◽  
Arshad Badfar
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Big Data Processing ◽  
Processing Mechanisms

NoSQL Databases

2014 ◽  
pp. 186-215 ◽  
Author(s):  
Ganesh Chandra Deka
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Open Source ◽  
Data Storage ◽  
Big Data Processing ◽  
Nosql Databases ◽  
Data Intensive ◽  
Huge Data ◽  
Data Intensive Applications

NoSQL databases are designed to meet the huge data storage requirements of cloud computing and big data processing. NoSQL databases have lots of advanced features in addition to the conventional RDBMS features. Hence, the “NoSQL” databases are popularly known as “Not only SQL” databases. A variety of NoSQL databases having different features to deal with exponentially growing data-intensive applications are available with open source and proprietary option. This chapter discusses some of the popular NoSQL databases and their features on the light of CAP theorem.

Big Data Analytics in Cloud Computing

2019 ◽  
pp. 325-341
Author(s):  
Rajganesh Nagarajan ◽  
Ramkumar Thirunavukarasu
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Data Visualization ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Future Research ◽  
Big Data Processing ◽  
Investment Cost

In this chapter, the authors consider different categories of data, which are processed by the big data analytics tools. The challenges with respect to the big data processing are identified and a solution with the help of cloud computing is highlighted. Since the emergence of cloud computing is highly advocated because of its pay-per-use concept, the data processing tools can be effectively deployed within cloud computing and certainly reduce the investment cost. In addition, this chapter talks about the big data platforms, tools, and applications with data visualization concept. Finally, the applications of data analytics are discussed for future research.

Trends and Technologies in Big Data Processing

2020 ◽  
pp. 17-42
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Computing Technology ◽  
Time Data ◽  
Big Data Processing ◽  
Real Time Data ◽  
Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

scholarly journals A survey on big data processing infrastructure: evolving role of FPGA

2015 ◽  
Vol 2 (3) ◽  
pp. 145 ◽  
Author(s):  
Krishna Chaitanya Nunna ◽  
Farhad Mehdipour ◽  
Antoine Trouvé ◽  
Kazuaki J. Murakami
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Big Data Processing

Big Data Processing in Cloud Computing Environments

2017 ◽  
Vol 23 (11) ◽  
pp. 11092-11095 ◽  
Author(s):  
A Noraziah ◽  
Mohammed Adam Ibrahim Fakherldin ◽  
Khalid Adam ◽  
Mazlina Abdul Majid
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Big Data Processing ◽  
Computing Environments

Resource Provisioning and Scheduling of Big Data Processing Jobs

2018 ◽  
pp. 382-401
Author(s):  
Rajni Aron ◽  
Deepak Kumar Aggarwal
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Research Area ◽  
Resource Provisioning ◽  
Time Data ◽  
Big Data Processing ◽  
Cloud Resource Management ◽  
Big Data Applications ◽  
Cloud Resource

Cloud Computing has become a buzzword in the IT industry. Cloud Computing which provides inexpensive computing resources on the pay-as-you-go basis is promptly gaining momentum as a substitute for traditional Information Technology (IT) based organizations. Therefore, the increased utilization of Clouds makes an execution of Big Data processing jobs a vital research area. As more and more users have started to store/process their real-time data in Cloud environments, Resource Provisioning and Scheduling of Big Data processing jobs becomes a key element of consideration for efficient execution of Big Data applications. This chapter discusses the fundamental concepts supporting Cloud Computing & Big Data terms and the relationship between them. This chapter will help researchers find the important characteristics of Cloud Resource Management Systems to handle Big Data processing jobs and will also help to select the most suitable technique for processing Big Data jobs in Cloud Computing environment.

Big Data Processing on Cloud Computing Using Hadoop Mapreduce and Apache Spark

2018 ◽  
pp. 224-250
Author(s):  
Yassir Samadi ◽  
Mostapha Zbakh ◽  
Amine Haouari
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Apache Spark ◽  
Big Data Processing ◽  
Data Intensive ◽  
Hadoop Mapreduce ◽  
Huge Data ◽  
Increasing Demand ◽  
Exponential Rates

Size of the data used by enterprises has been growing at exponential rates since last few years; handling such huge data from various sources is a challenge for Businesses. In addition, Big Data becomes one of the major areas of research for Cloud Service providers due to a large amount of data produced every day, and the inefficiency of traditional algorithms and technologies to handle these large amounts of data. In order to resolve the aforementioned problems and to meet the increasing demand for high-speed and data-intensive computing, several solutions have been developed by researches and developers. Among these solutions, there are Cloud Computing tools such as Hadoop MapReduce and Apache Spark, which work on the principles of parallel computing. This chapter focuses on how big data processing challenges can be handled by using Cloud Computing frameworks and the importance of using Cloud Computing by businesses

Sign in / Sign up

Export Citation Format

Share Document