Big Data Analytics for 5G Networks: Utilities, Frameworks, Challenges, and Opportunities

Wiley 5G Ref ◽  
2021 ◽  
pp. 1-38
Author(s):  
Azar Taufique ◽  
Ali Rizwan ◽  
Ali Imran ◽  
Kamran Arshad ◽  
Ahmed Zoha ◽  
...  
2019 ◽  
Vol 37 (7) ◽  
pp. 1690-1697 ◽  
Author(s):  
Muhammad Rehan Raza ◽  
Ahmad Rostami ◽  
Lena Wosinska ◽  
Paolo Monti

2022 ◽  
pp. 22-53
Author(s):  
Richard S. Segall ◽  
Gao Niu

Big Data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. This chapter discusses what Big Data is and its characteristics, and how this information revolution of Big Data is transforming our lives and the new technology and methodologies that have been developed to process data of these huge dimensionalities. This chapter discusses the components of the Big Data stack interface, categories of Big Data analytics software and platforms, descriptions of the top 20 Big Data analytics software. Big Data visualization techniques are discussed with real data from fatality analysis reporting system (FARS) managed by National Highway Traffic Safety Administration (NHTSA) of the United States Department of Transportation. Big Data web-based visualization software are discussed that are both JavaScript-based and user-interface-based. This chapter also discusses the challenges and opportunities of using Big Data and presents a flow diagram of the 30 chapters within this handbook.


2015 ◽  
Author(s):  
I. H. F. Santos ◽  
M. M. Machado ◽  
E. E. Russo ◽  
D. M. Manguinho ◽  
V. T. Almeida ◽  
...  

Author(s):  
Abhishek Bajpai ◽  
Dr. Sanjiv Sharma

As the Volume of the data produced is increasing day by day in our society, the exploration of big data in healthcare is increasing at an unprecedented rate. Now days, Big data is very popular buzzword concept in the various areas. This paper provide an effort is made to established that even the healthcare industries are stepping into big data pool to take all advantages from its various advanced tools and technologies. This paper provides the review of various research disciplines made in health care realm using big data approaches and methodologies. Big data methodologies can be used for the healthcare data analytics (which consist 4 V’s) which provide the better decision to accelerate the business profit and customer affection, acquire a better understanding of market behaviours and trends and to provide E-Health services using Digital imaging and communication in Medicine (DICOM).Big data Techniques like Map Reduce, Machine learning can be applied to develop system for early diagnosis of disease, i.e. analysis of the chronic disease like- heart disease, diabetes and stroke. The analysis on the data is performed using big data analytics framework Hadoop. Hadoop framework is used to process large data sets Further the paper present the various Big data tools , challenges and opportunities and various hurdles followed by the conclusion.                                      


Author(s):  
Richard S. Segall ◽  
Gao Niu

Big Data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. This chapter discusses what Big Data is and its characteristics, and how this information revolution of Big Data is transforming our lives and the new technology and methodologies that have been developed to process data of these huge dimensionalities. This chapter discusses the components of the Big Data stack interface, categories of Big Data analytics software and platforms, descriptions of the top 20 Big Data analytics software. Big Data visualization techniques are discussed with real data from fatality analysis reporting system (FARS) managed by National Highway Traffic Safety Administration (NHTSA) of the United States Department of Transportation. Big Data web-based visualization software are discussed that are both JavaScript-based and user-interface-based. This chapter also discusses the challenges and opportunities of using Big Data and presents a flow diagram of the 30 chapters within this handbook.


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