Software Tools and Techniques for Big Data Computing in Healthcare Clouds

2015 ◽  
Vol 43-44 ◽  
pp. 38-39 ◽  
Author(s):  
Lizhe Wang ◽  
Rajiv Ranjan ◽  
Joanna Kołodziej ◽  
Albert Zomaya ◽  
Leila Alem
Author(s):  
Manbir Sandhu ◽  
Purnima, Anuradha Saini

Big data is a fast-growing technology that has the scope to mine huge amount of data to be used in various analytic applications. With large amount of data streaming in from a myriad of sources: social media, online transactions and ubiquity of smart devices, Big Data is practically garnering attention across all stakeholders from academics, banking, government, heath care, manufacturing and retail. Big Data refers to an enormous amount of data generated from disparate sources along with data analytic techniques to examine this voluminous data for predictive trends and patterns, to exploit new growth opportunities, to gain insight, to make informed decisions and optimize processes. Data-driven decision making is the essence of business establishments. The explosive growth of data is steering the business units to tap the potential of Big Data to achieve fueling growth and to achieve a cutting edge over their competitors. The overwhelming generation of data brings with it, its share of concerns. This paper discusses the concept of Big Data, its characteristics, the tools and techniques deployed by organizations to harness the power of Big Data and the daunting issues that hinder the adoption of Business Intelligence in Big Data strategies in organizations.


2016 ◽  
Vol 11 (2) ◽  
pp. 252-264
Author(s):  
Weidong Qiu ◽  
Bozhong Liu ◽  
Can Ge ◽  
Lingzhi Xu ◽  
Xiaoming Tang ◽  
...  

CHANCE ◽  
2013 ◽  
Vol 26 (2) ◽  
pp. 28-32 ◽  
Author(s):  
Nicole Lazar

2014 ◽  
Vol 23 (01) ◽  
pp. 177-181 ◽  
Author(s):  
W. Hersh ◽  
A. U. Jai Ganesh ◽  
P. Otero

Summary Objective: The growing volume and diversity of health and biomedical data indicate that the era of Big Data has arrived for healthcare. This has many implications for informatics, not only in terms of implementing and evaluating information systems, but also for the work and training of informatics researchers and professionals. This article addresses the question: What do biomedical and health informaticians working in analytics and Big Data need to know? Methods: We hypothesize a set of skills that we hope will be discussed among academic and other informaticians. Results: The set of skills includes: Programming - especially with data-oriented tools, such as SQL and statistical programming languages; Statistics - working knowledge to apply tools and techniques; Domain knowledge - depending on one’s area of work, bioscience or health care; and Communication - being able to understand needs of people and organizations, and articulate results back to them. Conclusion: Biomedical and health informatics educational programs must introduce concepts of analytics, Big Data, and the underlying skills to use and apply them into their curricula. The development of new coursework should focus on those who will become experts, with training aiming to provide skills in “deep analytical talent” as well as those who need knowledge to support such individuals.


Author(s):  
Luiz Angelo Steffenel ◽  
Manuele Kirsch Pinheiro ◽  
Lucas Vaz Peres ◽  
Damaris Kirsch Pinheiro

The exponential dissemination of proximity computing devices (smartphones, tablets, nanocomputers, etc.) raises important questions on how to transmit, store and analyze data in networks integrating those devices. New approaches like edge computing aim at delegating part of the work to devices in the “edge” of the network. In this article, the focus is on the use of pervasive grids to implement edge computing and leverage such challenges, especially the strategies to ensure data proximity and context awareness, two factors that impact the performance of big data analyses in distributed systems. This article discusses the limitations of traditional big data computing platforms and introduces the principles and challenges to implement edge computing over pervasive grids. Finally, using CloudFIT, a distributed computing platform, the authors illustrate the deployment of a real geophysical application on a pervasive network.


Hadmérnök ◽  
2020 ◽  
Vol 15 (4) ◽  
pp. 141-158
Author(s):  
Eszter Katalin Bognár

In modern warfare, the most important innovation to date has been the utilisation of information as a  weapon. The basis of successful military operations is  the ability to correctly assess a situation based on  credible collected information. In today’s military, the primary challenge is not the actual collection of data.  It has become more important to extract relevant  information from that data. This requirement cannot  be successfully completed without necessary  improvements in tools and techniques to support the acquisition and analysis of data. This study defines  Big Data and its concept as applied to military  reconnaissance, focusing on the processing of  imagery and textual data, bringing to light modern  data processing and analytics methods that enable  effective processing.


2020 ◽  
Vol 10 (4) ◽  
pp. 36
Author(s):  
Sajeewan Pratsri ◽  
Prachyanun Nilsook

According to a continuously increasing amount of information in all aspects whether the sources are retrieved from an internal or external organization, a platform should be provided for the automation of whole processes in the collection, storage, and processing of Big Data. The tool for creating Big Data is a Big Data challenge. Furthermore, the security and privacy of Big Data and Big Data analysis in organizations, government agencies, and educational institutions also have an impact on the aspect of designing a Big Data platform for higher education institute (HEi). It is a digital learning platform that is an online instruction and the use of digital media for educational reform including a module provides information on functions of various modules between computers and humans. 1) Big Data architecture is a framework for an architecture of numerous data which consisting of Big Data Infrastructure (BDI), Data Storage (Cloud-based), processing of a computer system that uses all parts of computer resources for optimal efficiency (High-Performance Computing: HPC), a network system to detect the target device network. Thereafter, according to Hadoop’s tools and techniques, when Big Data was introduced with Hadoop's tools and techniques, the benefits of the Big Data platform would provide desired data analysis by retrieving existing information, to illustrate, student information and teaching information that is large amounts of information to adopt for accurate forecasting.


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