Big Data: Trends, Challenges, Opportunities, Tools, Success Factors, and the Way Toward Pandemic Analytics

2021 ◽  
pp. 297-318
Author(s):  
P. R. Anisha ◽  
C. Kishor Kumar Reddy ◽  
Nguyen Gia Nhu
Keyword(s):  
Big Data ◽  
Success Factors ◽  
The Way

Artistic Challenges within Control Societies: Big Data and Democratic Resistance

MedienJournal ◽  
2017 ◽  
Vol 38 (4) ◽  
pp. 50-61 ◽  
Author(s):  
Jan Jagodzinski
Keyword(s):  
Big Data ◽  
Gilles Deleuze ◽  
Data Archive ◽  
Current State ◽  
The Future ◽  
The Way

This paper will first briefly map out the shift from disciplinary to control societies (what I call designer capitalism, the idea of control comes from Gilles Deleuze) in relation to surveillance and mediation of life through screen cultures. The paper then shifts to the issues of digitalization in relation to big data that have the danger of continuing to close off life as zoë, that is life that is creative rather than captured via attention technologies through marketing techniques and surveillance. The last part of this paper then develops the way artists are able to resist the big data archive by turning the data in on itself to offer viewers and participants a glimpse of the current state of manipulating desire and maintaining copy right in order to keep the future closed rather than being potentially open.

scholarly journals CoPart: a context-based partitioning technique for big data

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sara Migliorini ◽  
Alberto Belussi ◽  
Elisa Quintarelli ◽  
Damiano Carra
Keyword(s):  
Big Data ◽  
Quality Criteria ◽  
Query Execution ◽  
Data Correlation ◽  
Huge Amount ◽  
Programming Paradigm ◽  
Computation Node ◽  
Contextual Dimension ◽  
Partitioning Technique ◽  
The Way

AbstractThe MapReduce programming paradigm is frequently used in order to process and analyse a huge amount of data. This paradigm relies on the ability to apply the same operation in parallel on independent chunks of data. The consequence is that the overall performances greatly depend on the way data are partitioned among the various computation nodes. The default partitioning technique, provided by systems like Hadoop or Spark, basically performs a random subdivision of the input records, without considering the nature and correlation between them. Even if such approach can be appropriate in the simplest case where all the input records have to be always analyzed, it becomes a limit for sophisticated analyses, in which correlations between records can be exploited to preliminarily prune unnecessary computations. In this paper we design a context-based multi-dimensional partitioning technique, called CoPart, which takes care of data correlation in order to determine how records are subdivided between splits (i.e., units of work assigned to a computation node). More specifically, it considers not only the correlation of data w.r.t. contextual attributes, but also the distribution of each contextual dimension in the dataset. We experimentally compare our approach with existing ones, considering both quality criteria and the query execution times.

The way forward for big data analysis in ophthalmology and medicine

2016 ◽  
Vol 1 ◽  
pp. 19-19
Author(s):  
Stephen G. Odaibo ◽  
David G. Odaibo
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
The Way

Big Data Analytics in the Healthcare Industry

2020 ◽  
pp. 160-178
Author(s):  
Arulkumar Varatharajan ◽  
Selvan C. ◽  
Vimalkumar Varatharajan
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Human Services ◽  
Big Data Analytics ◽  
Healthcare Industry ◽  
Multimodal Data ◽  
Design Structure ◽  
Costs Of Treatment ◽  
The Way

Big Data has changed the way we manage, analyze and impact the data information in any industry. A champion among the most promising zones where it will, in general, be associated with takeoff progress is therapeutic medicinal administrations. Administration examinations can diminish costs of treatment, foresee flare-ups of pestilences, keep up a key separation from preventable diseases and improve individual fulfillment overall. The chapter depicts the beginning field of a huge information investigation in human services, talks about the advantages, diagrams a design structure and approach, portrays models revealed in the writing, quickly examines the difficulties, and offers ends. A continuous examination which targets the utilization of tremendous volumes of remedial data information while combining multimodal data information from various sources is discussed. Potential locales of research inside this field which can give noteworthy impact on medicinal administrations movement are in like manner dissected.

Records Management in the Fourth Industrial Revolution

2021 ◽  
pp. 1-24
Author(s):  
Adeyinka Tella ◽  
Oluwakemi Titilola Olaniyi ◽  
Aderinola Ololade Dunmade
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Industrial Revolution ◽  
Records Management ◽  
Technological Advancement ◽  
Fourth Industrial Revolution ◽  
Industrial Revolutions ◽  
The Way

The chapter looked at records management in the fourth industrial revolution (4IR) with the challenges and the way forward. The chapter discussed the industrial revolutions, records management, and the fourth industrial revolution (4IR), and described the advancement in records management in the 4IR based on the 4IR tools and technologies including artificial intelligence, blockchain, internet of things (IoT), robotics, and big data. The chapter also identified and discussed the benefits of technological advancement in the management of records; challenges of records management at the wake of 4IR and charted the way forward. In the context of document and records management, and taking into account all characteristics of the 4IR technologies and tools as well as its underlying technologies and concepts, the chapter concluded that the 4IR tools can be used to save time to create and process records, secure records from being damaged or destroyed, confirm the integrity of records, among others.

scholarly journals Sensing Possibility in International Law – Concepts and Categories for the 21st Century: A Response to Fleur Johns

AJIL Unbound ◽  
2017 ◽  
Vol 111 ◽  
pp. 200-204
Author(s):  
Keith Culver
Keyword(s):  
Big Data ◽  
International Law ◽  
21St Century ◽  
Concepts And Categories ◽  
The World ◽  
Algorithmic Analysis ◽  
The Way

Fleur Johns raises the alarm regarding the potential for algorithmic analysis of big data to change fundamentally the way international lawyers and their allies gather and interpret facts to which international law is applied. Johns invites her readers to join her in seeking ways to save the aspirations of law on the “global plane” from these disruptive forces. In what follows I take up Johns’ invitation, in the spirit of its advancing claims “in a speculative or polemical mode,” asking the reader to withhold for a moment demands for completeness, instead joining in exploration of how the world of international law might be viewed differently if a larger version of Johns’ argument holds.

scholarly journals Big Data and Business Analytics: Trends, Platforms, Success Factors and Applications

2019 ◽  
Vol 3 (2) ◽  
pp. 32 ◽  
Author(s):  
Ifeyinwa Angela Ajah ◽  
Henry Friday Nweke
Keyword(s):  
Big Data ◽  
Success Factors ◽  
Database Management System ◽  
Unstructured Data ◽  
Digital Data ◽  
Business Strategies ◽  
Modern World ◽  
Successful Implementation ◽  
Business Analytics ◽  
Business World

Big data and business analytics are trends that are positively impacting the business world. Past researches show that data generated in the modern world is huge and growing exponentially. These include structured and unstructured data that flood organizations daily. Unstructured data constitute the majority of the world’s digital data and these include text files, web, and social media posts, emails, images, audio, movies, etc. The unstructured data cannot be managed in the traditional relational database management system (RDBMS). Therefore, data proliferation requires a rethinking of techniques for capturing, storing, and processing the data. This is the role big data has come to play. This paper, therefore, is aimed at increasing the attention of organizations and researchers to various applications and benefits of big data technology. The paper reviews and discusses, the recent trends, opportunities and pitfalls of big data and how it has enabled organizations to create successful business strategies and remain competitive, based on available literature. Furthermore, the review presents the various applications of big data and business analytics, data sources generated in these applications and their key characteristics. Finally, the review not only outlines the challenges for successful implementation of big data projects but also highlights the current open research directions of big data analytics that require further consideration. The reviewed areas of big data suggest that good management and manipulation of the large data sets using the techniques and tools of big data can deliver actionable insights that create business values.

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