Big Data in Healthcare: Technical Challenges and Opportunities

Author(s):  
Ganesh M. Kakandikar ◽  
Vilas M. Nandedkar
Author(s):  
Maya Gopal P.S. ◽  
Bhargavi Renta Chintala

This article reviews various aspects of research concerning the background and state-of-the-art of big data in agriculture. This article focuses on data generation, storage, analysis and visualization in big data. In every phase, technical challenges and the latest advancement are discussed, and these discussions aim to provide a comprehensive overview and complete picture of this exciting area. This survey is concluded with a discussion on the application of big data in precision agriculture and its future directions.


2014 ◽  
Author(s):  
A. Maliardi ◽  
F. Cecconi ◽  
D. Simeone ◽  
S. Gumarov ◽  
T. Shokanov ◽  
...  

Author(s):  
Philip Habel ◽  
Yannis Theocharis

In the last decade, big data, and social media in particular, have seen increased popularity among citizens, organizations, politicians, and other elites—which in turn has created new and promising avenues for scholars studying long-standing questions of communication flows and influence. Studies of social media play a prominent role in our evolving understanding of the supply and demand sides of the political process, including the novel strategies adopted by elites to persuade and mobilize publics, as well as the ways in which citizens react, interact with elites and others, and utilize platforms to persuade audiences. While recognizing some challenges, this chapter speaks to the myriad of opportunities that social media data afford for evaluating questions of mobilization and persuasion, ultimately bringing us closer to a more complete understanding Lasswell’s (1948) famous maxim: “who, says what, in which channel, to whom, [and] with what effect.”


2020 ◽  
Vol 26 (11) ◽  
pp. 6040-6061 ◽  
Author(s):  
Jianyang Xia ◽  
Jing Wang ◽  
Shuli Niu

2015 ◽  
pp. 180-216 ◽  
Author(s):  
Suzhi Bi ◽  
Rui Zhang ◽  
Zhi Ding ◽  
Shuguang Cui

Author(s):  
Shivom Aggarwal ◽  
Abhishek Nayak

Mobile technologies have given rise to tremendous amounts of data in real-time, which can be unstructured and uncertain. This growth can be attributed as Mobile Big Data and provides new challenges and opportunities for innovation. This chapter attempts to define the concept of Mobile Big Data, provide description of various sources of Mobile Big Data and discuss SWAI (Sources Warehousing Analytics Insights) model of Big Data processing. To understand this complex concept, it is important to visualize the Big Data ecosystem, respective players. Moreover, mobile computing, Internet of things, and other associated technologies have been discussed in light of marketing and communications based applications. The current trends in Mobile Big Data and associated value chain help us understand where the next frontiers of innovation are and how one can create value. This is linked to the future aspects of the Mobile Big Data and evolution of technologies from now onwards.


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