scholarly journals TRANSVAC workshop on standardisation and harmonisation of analytical platforms for HIV, TB and malaria vaccines: ‘How can big data help?’

Vaccine ◽  
2014 ◽  
Vol 32 (35) ◽  
pp. 4365-4368 ◽  
Author(s):  
Céline Dutruel ◽  
Jelle Thole ◽  
Mark Geels ◽  
Hans-Joachim Mollenkopf ◽  
Tom Ottenhoff ◽  
...  
Keyword(s):  
Big Data ◽  
Malaria Vaccines ◽  
Analytical Platforms

scholarly journals Big Data and digital economy

2020 ◽  
pp. 187-197
Author(s):  
Sergey Belov ◽  
Daria Zrelova ◽  
Vladimir Korenkov
Keyword(s):  
Big Data ◽  
Information Systems ◽  
Data Processing ◽  
Economic Research ◽  
Distributed Information Systems ◽  
Research Teams ◽  
Distributed Information ◽  
New Knowledge ◽  
Data Ecosystem ◽  
Analytical Platforms

In this paper, Big Data is considered as an "umbrella" term that combines various concepts, technologies and methods of data processing in distributed information systems that provide a qualitatively new useful information (new knowledge). The stages of "standard" research in the Big Data approach are described. A brief description of the Big Data ecosystem, which consists of several main categories, is given. Various projects and initiatives at the national and international levels are considered, as well as examples of the use of Big Data in business, economy, and society. As concrete examples of the construction and use of analytical platforms for Big Data, successful socio-economic research carried out by the authors as part of research teams at the Plekhanov Russian University of Economics is presented. The Big data metaphor is certainly successful, since it naturally connects a complex of concepts, technologies and methods of Big data with the economy by hinting at a connection with other well-known metaphors –"Big oil", "Big ore", etc.

scholarly journals Experimental Characteristics Study of Data Storage Formats for Data Marts Development within Data Lakes

2021 ◽  
Vol 11 (18) ◽  
pp. 8651
Author(s):  
Vladimir Belov ◽  
Alexander N. Kosenkov ◽  
Evgeny Nikulchev
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Storage System ◽  
Apache Hadoop ◽  
Aggregated Data ◽  
Data Marts ◽  
Hadoop Platform ◽  
Analytical Platforms ◽  
Big Data Storage

One of the most popular methods for building analytical platforms involves the use of the concept of data lakes. A data lake is a storage system in which the data are presented in their original format, making it difficult to conduct analytics or present aggregated data. To solve this issue, data marts are used, representing environments of stored data of highly specialized information, focused on the requests of employees of a certain department, the vector of an organization’s work. This article presents a study of big data storage formats in the Apache Hadoop platform when used to build data marts.

A Survey of Big Data Analytics Systems

2014 ◽  
pp. 392-418 ◽  
Author(s):  
M. Baby Nirmala
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Processing System ◽  
Full Potential ◽  
Analytical Processing ◽  
Tools And Techniques ◽  
New Generation ◽  
Analytical Platforms

In this emerging era of analytics 3.0, where big data is the heart of talk in all sectors, achieving and extracting the full potential from this vast data is accomplished by many vendors through their new generation analytical processing systems. This chapter deals with a brief introduction of the categories of analytical processing system, followed by some prominent analytical platforms, appliances, frameworks, engines, fabrics, solutions, tools, and products of the big data vendors. Finally, it deals with big data analytics in the network, its security, WAN optimization tools, and techniques for cloud-based big data analytics.

A Survey of Big Data Analytics Systems

Big Data ◽  
2016 ◽  
pp. 1024-1052
Author(s):  
M. Baby Nirmala
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Processing System ◽  
Full Potential ◽  
Analytical Processing ◽  
Tools And Techniques ◽  
New Generation ◽  
Analytical Platforms

In this emerging era of analytics 3.0, where big data is the heart of talk in all sectors, achieving and extracting the full potential from this vast data is accomplished by many vendors through their new generation analytical processing systems. This chapter deals with a brief introduction of the categories of analytical processing system, followed by some prominent analytical platforms, appliances, frameworks, engines, fabrics, solutions, tools, and products of the big data vendors. Finally, it deals with big data analytics in the network, its security, WAN optimization tools, and techniques for cloud-based big data analytics.

Find Out About 'Big Data' to Track Outcomes

ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  
Big Data

Find Out About 'Big Data' to Track Outcomes

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

“Big Data in Psychology: Methods and Applications”

2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  
Big Data

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org

When the Sample Is the Population: Big Data

PsycCRITIQUES ◽  
2014 ◽  
Vol 59 (2) ◽  
Author(s):  
David J. Pittenger
Keyword(s):  
Big Data
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