Big Data Analyses and New Technology Applications in Sport Management, an Overview

2020 ◽  
Author(s):  
Leonardo Jose Mataruna-Dos-Santos ◽  
Alessio Faccia ◽  
Hussein Muñoz Helú ◽  
Mohammed Sayeed Khan
Keyword(s):  
Big Data ◽  
Sport Management ◽  
New Technology ◽  
Data Analyses ◽  
Technology Applications

scholarly journals The European Big Data Value Ecosystem

2021 ◽  
pp. 3-19
Author(s):  
Edward Curry ◽  
Andreas Metzger ◽  
Sonja Zillner ◽  
Jean-Christophe Pazzaglia ◽  
Ana García Robles ◽  
...  
Keyword(s):  
Big Data ◽  
Business Models ◽  
New Technology ◽  
Business Policy ◽  
Efficient Operation ◽  
Research And Innovation ◽  
Data Value ◽  
Technology Applications ◽  
Data Ecosystem ◽  
Value Association

AbstractThe adoption of big data technology within industrial sectors facilitates organizations to gain competitive advantage. The impacts of big data go beyond the commercial world, creating significant societal impact, from improving healthcare systems to the energy-efficient operation of cities and transportation infrastructure, to increasing the transparency and efficiency of public administration. In order to exploit the potential of big data to create value for society, citizens and businesses, Europe needs to embrace new technology, applications, use cases and business models within and across various sectors and domains. In the early part of the 2010s, a clear strategy centring around the notion of the European Big Data Value Ecosystem started to take form with the aim of increasing the competitiveness of European industries through a data ecosystem which tackles the fundamental elements of big data value, including the ecosystem, research and innovation, business, policy and regulation, and the emerging elements of data-driven AI and common European data spaces. This chapter describes the big data value ecosystem and its strategic importance. It details the challenges of creating this ecosystem and outlines the vision and strategy of the Big Data Value Public-Private Partnership and the Big Data Value Association, which together formed the core of the ecosystem, to make Europe the world leader in the creation of big data value. Finally, it details the elements of big data value which were addressed to realise this vision.

Big Data Analyses of Korea's Nation Branding on Google and Facebook

2020 ◽  
Vol 51 (1) ◽  
pp. 151-174
Author(s):  
Chung Joo Chung ◽  
Yunna Rhee ◽  
Heewon Cha
Keyword(s):  
Big Data ◽  
Nation Branding ◽  
Data Analyses

Exploring Support Vector Machines for Big Data Analyses

2021 ◽  
Author(s):  
Siyang Lu ◽  
Yihong Chen ◽  
Xiaolin Zhu ◽  
Ziyi Wang ◽  
Yangjun Ou ◽  
...  
Keyword(s):  
Big Data ◽  
Support Vector Machines ◽  
Support Vector ◽  
Data Analyses ◽  
Vector Machines

scholarly journals Research the Systems Architecture and Technology of Wisdom Community Based on the Internet of Things

2012 ◽  
Vol 6-7 ◽  
pp. 957-963 ◽  
Author(s):  
Shun Bing Zhu ◽  
Chun Quan Du ◽  
Miao Miao Niu
Keyword(s):  
Internet Of Things ◽  
Social Services ◽  
New Technology ◽  
Basic Unit ◽  
The Internet ◽  
Mutual Aid ◽  
Systems Architecture ◽  
Computing Platform ◽  
Technology Applications ◽  
The Internet Of Things

The wisdom community is the basic unit of the smart city, is a set of urban management, public services, social services, residents’ autonomy and mutual aid services in one of the new technology applications. This article analyzes the current situation and existing problems of the wisdom community, then described the Internet of Things architecture, equipment features, community cloud computing platform and structure, the last detailed analysis of the wisdom community features and community network video intercom, home security, appliance control, non-contact card access control, card consumption management, community security, community e-service technology and other technical content and features.

scholarly journals Is Big Data Security Essential for Students to Understand?

2020 ◽  
Vol 11 (2) ◽  
pp. 161-170
Author(s):  
Rochman Hadi Mustofa
Keyword(s):  
Big Data ◽  
Undergraduate Students ◽  
Data Security ◽  
Personal Data ◽  
Digital Data ◽  
Security And Privacy ◽  
Group Discussions ◽  
Technology Applications ◽  
Digital Payments ◽  
Financial Technology

AbstractBig Data has become a significant concern of the world, along with the era of digital transformation. However, there are still many young people, especially in developing countries, who are not yet aware of the security of their big data, especially personal data. Misuse of information from big data often results in violations of privacy, security, and cybercrime. This study aims to determine how aware of the younger generation of security and privacy of their big data. Data were collected qualitatively by interviews and focus group discussions (FGD) from. Respondents were undergraduate students who used social media and financial technology applications such as online shopping, digital payments, digital wallet and hotel/transportation booking applications. The results showed that students were not aware enough and understood the security or privacy of their digital data, and some respondents even gave personal data to potentially scam sites. Most students are not careful in providing big data information because they are not aware of the risks behind it, socialization is needed in the future as a step to prevent potential data theft.

scholarly journals BIG DATA FOR RISK ANALYSIS: THE FUTURE OF SAFE RAILWAYS

2016 ◽  
Author(s):  
Miguel Figueres Esteban
Keyword(s):  
Big Data ◽  
Risk Analysis ◽  
Safety Management ◽  
New Technology ◽  
Data Sources ◽  
Transport Systems ◽  
Text Documents ◽  
Railway Systems ◽  
Wide Range ◽  
Three Components

New technology brings ever more data to support decision-making for intelligent transport systems. Big Data is no longer a futuristic challenge, it is happening right now: modern railway systems have countless sources of data providing a massive quantity of diverse information on every aspect of operations such as train position and speed, brake applications, passenger numbers, status of the signaling system or reported incidents.The traditional approaches to safety management on the railways have relied on static data sources to populate traditional safety tools such as bow-tie models and fault trees. The Big Data Risk Analysis (BDRA) program for Railways at the University of Huddersfield is investigating how the many Big Data sources from the railway can be combined in a meaningful way to provide a better understanding about the GB railway systems and the environment within which they operate.Moving to BDRA is not simply a matter of scaling-up existing analysis techniques. BDRA has to coordinate and combine a wide range of sources with different types of data and accuracy, and that is not straight-forward. BDRA is structured around three components: data, ontology and visualisation. Each of these components is critical to support the overall framework. This paper describes how these three components are used to get safety knowledge from two data sources by means of ontologies from text documents. This is a part of the ongoing BDRA research that is looking at integrating many large and varied data sources to support railway safety and decision-makers.DOI: http://dx.doi.org/10.4995/CIT2016.2016.1825

The impact of big data on innovation and value generation in pharmaceutical sales and marketing

2021 ◽  
Vol 3 (2) ◽  
pp. 37-52
Author(s):  
Antonio Pesqueira
Keyword(s):  
Big Data ◽  
New Technology ◽  
Unmet Need ◽  
Pharmaceutical Companies ◽  
Future Trends ◽  
Pharmaceutical Sales ◽  
Sales And Marketing ◽  
Investment Opportunities ◽  
Application Fields ◽  
The Impact

Using Big Data in the pharmaceutical industry is a relatively new technology, and the benefits and applications are yet to be understood. There are some cases currently being piloted, but others have already been adopted by some pharmaceutical organizations, proving the unmet need in a field that is still in its infancy. This paper aims to understand how and if Big Data can contribute to commercial innovation, as well as future trends, investment opportunities. Participants from 26 pharmaceutical companies participated in different focus groups where topics were grouped by individuals and evaluation areas were discussed to discover any potential connections between Big Data and Innovation in commercial pharmaceutical environments. This study used the collected data to analyze and draw conclusions about how many life sciences leaders and professionals already know about Big Data and are identifying examples and processes where Big data is supporting and generating innovation. In addition, we were able to understand that the industry is already comfortable with Big Data, and there were some very accurate research results regarding the most pertinent application fields and key considerations moving forward. Using the network analysis findings and the relationships and connections explained by respondents, we can reveal how Big Data and innovation are interconnected.

scholarly journals ASAP 2020 update: an open, scalable and interactive web-based portal for (single-cell) omics analyses

2020 ◽  
Vol 48 (W1) ◽  
pp. W403-W414
Author(s):  
Fabrice P A David ◽  
Maria Litovchenko ◽  
Bart Deplancke ◽  
Vincent Gardeux
Keyword(s):  
Big Data ◽  
Single Cell ◽  
Single Cell Analysis ◽  
Omics Data ◽  
Cell Analysis ◽  
Rna Seq ◽  
Analysis Pipeline ◽  
Web Based ◽  
Data Analyses ◽  
The Web

Abstract Single-cell omics enables researchers to dissect biological systems at a resolution that was unthinkable just 10 years ago. However, this analytical revolution also triggered new demands in ‘big data’ management, forcing researchers to stay up to speed with increasingly complex analytical processes and rapidly evolving methods. To render these processes and approaches more accessible, we developed the web-based, collaborative portal ASAP (Automated Single-cell Analysis Portal). Our primary goal is thereby to democratize single-cell omics data analyses (scRNA-seq and more recently scATAC-seq). By taking advantage of a Docker system to enhance reproducibility, and novel bioinformatics approaches that were recently developed for improving scalability, ASAP meets challenging requirements set by recent cell atlasing efforts such as the Human (HCA) and Fly (FCA) Cell Atlas Projects. Specifically, ASAP can now handle datasets containing millions of cells, integrating intuitive tools that allow researchers to collaborate on the same project synchronously. ASAP tools are versioned, and researchers can create unique access IDs for storing complete analyses that can be reproduced or completed by others. Finally, ASAP does not require any installation and provides a full and modular single-cell RNA-seq analysis pipeline. ASAP is freely available at https://asap.epfl.ch.

Applications of Big Data in Large and Small Systems

2021 ◽  
pp. 20-37
Author(s):  
Archana Purwar ◽  
Indu Chawla
Keyword(s):  
Big Data ◽  
Soft Computing ◽  
New Technology ◽  
Electronic Devices ◽  
Small Systems ◽  
Innovative Methods ◽  
Research Challenges ◽  
Basic Understanding ◽  
Basic Concepts ◽  
Tools And Techniques

Nowadays, big data is available in every field due to the advent of computers and electronic devices and the advancement of technology. However, analysis of this data requires new technology as the earlier designed traditional tools and techniques are not sufficient. There is an urgent need for innovative methods and technologies to resolve issues and challenges. Soft computing approaches have proved successful in handling voluminous data and generating solutions for them. This chapter focuses on basic concepts of big data along with the fundamental of various soft computing approaches that give a basic understanding of three major soft computing paradigms to students. It further gives a combination of these approaches namely hybrid soft computing approaches. Moreover, it also poses different applications dealing with big data where soft computing approaches are being successfully used. Further, it comes out with research challenges faced by the community of researchers.

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