scholarly journals Big Data Analytics Application Model Based on Data Quality Dimensions and Big Data Traits in Public Sector

2020 ◽  
Vol 9 (2) ◽  
pp. 1247-1256
Author(s):  
Muslihah Wook
Keyword(s):  
Big Data ◽  
Public Sector ◽  
Data Quality ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Model Based ◽  
Application Model ◽  
Quality Dimensions ◽  
Data Quality Dimensions

scholarly journals Exploring big data traits and data quality dimensions for big data analytics application using partial least squares structural equation modelling

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Muslihah Wook ◽  
Nor Asiakin Hasbullah ◽  
Norulzahrah Mohd Zainudin ◽  
Zam Zarina Abdul Jabar ◽  
Suzaimah Ramli ◽  
...  
Keyword(s):  
Big Data ◽  
Data Quality ◽  
Least Squares ◽  
Structural Equation Modelling ◽  
Data Analytics ◽  
Structural Equation ◽  
Big Data Analytics ◽  
Equation Modelling ◽  
Quality Dimensions ◽  
Data Quality Dimensions

AbstractThe popularity of big data analytics (BDA) has boosted the interest of organisations into exploiting their large scale data. This technology can become a strategic stimulation for organisations to achieve competitive advantage and sustainable growth. Previous BDA research, however, has focused more on introducing more traits, known as Vs for big data traits, while ignoring the quality of data when examining the application of BDA. Therefore, this study aims to explore the effect of big data traits and data quality dimensions on BDA application. This study has formulated 10 hypotheses that comprised of the relationships of big data traits, accuracy, believability, completeness, timeliness, ease of operation, and BDA application constructs. This study conducted a survey using a questionnaire as a data collection instrument. Then, the partial least squares structural equation modelling technique was used to analyse the hypothesised relationships between the constructs. The findings revealed that big data traits can significantly affect all constructs for data quality dimensions and that the ease of operation construct has a significant effect on BDA application. This study contributes to the literature by bringing new insights to the field of BDA and may serve as a guideline for future researchers and practitioners when studying BDA application.

ESTABLISHMENT OF BIG DATA ANALYTICS APPLICATION MODEL FOR MALAYSIAN PUBLIC SECTOR: AN EXPERT VALIDATION

EDPACS ◽  
2021 ◽  
pp. 1-20
Author(s):  
Zam Zarina Abdul Jabar ◽  
Muslihah Wook ◽  
Omar Zakaria ◽  
Suzaimah Ramli ◽  
Noor Afiza Mat Razali
Keyword(s):  
Big Data ◽  
Public Sector ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Application Model ◽  
Expert Validation

Big data to knowledge – Harnessing semiotic relationships of data quality and skills in genome curation work

2018 ◽  
Vol 44 (6) ◽  
pp. 785-801
Author(s):  
Hong Huang
Keyword(s):  
Quality Assurance ◽  
Big Data ◽  
Data Quality ◽  
Strong Support ◽  
Policy Makers ◽  
Specific Data ◽  
Theoretical Perspectives ◽  
Funding Agencies ◽  
Quality Dimensions ◽  
Data Quality Dimensions

This article aims to understand the views of genomic scientists with regard to the data quality assurances associated with semiotics and data–information–knowledge (DIK). The resulting communication of signs generated from genomic curation work, was found within different semantic levels of DIK that correlate specific data quality dimensions with their respective skills. Syntactic data quality dimensions were ranked the highest among all other semiotic data quality dimensions, which indicated that scientists spend great efforts for handling data wrangling activities in genome curation work. Semantic- and pragmatic-related sign communications were about meaningful interpretation, thus required additional adaptive and interpretative skills to deal with data quality issues. This expanded concept of ‘curation’ as sign/semiotic was not previously explored from the practical to the theoretical perspectives. The findings inform policy makers and practitioners to develop framework and cyberinfrastructure that facilitate the initiatives and advocacies of ‘Big Data to Knowledge’ by funding agencies. The findings from this study can also help plan data quality assurance policies and thus maximise the efficiency of genomic data management. Our results give strong support to the relevance of data quality skills communication for relationship with data quality assurance in genome curation activities.

scholarly journals Model-based Big Data Analytics-as-a-Service: Take Big Data to the Next Level

2018 ◽  
pp. 1-1 ◽  
Author(s):  
Claudio Agostino Ardagna ◽  
Valerio Bellandi ◽  
Michele Bezzi ◽  
Paolo Ceravolo ◽  
Ernesto Damiani ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Model Based

scholarly journals Big Data and Algorithms in the Public Sector and Their Impact on the Transparency of Decision-Making

2018 ◽  
Vol 331 ◽  
pp. 301-311
Author(s):  
Gergely László Szὄke
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Public Sector ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Legal Framework ◽  
New Wave ◽  
Short Introduction ◽  
The Public ◽  
Potential Use

Big Data is clearly one of the most used buzzwords nowadays, but it really seems that the phenomenon of Big Data will have a huge effect on many different fields, and may be regarded as the new wave of the information revolution started in the 60s of the last century. The potential of exploiting Big Data promises significant benefits (and also new challenges) both in the private and the public sector – this essay will focus on this latter. After a short introduction about Big Data, this paper will first sum up the potential use of Big Data analytics in the public sector. Then I will focus on a specific issue within this scope, namely, how the use of Big Data and algorithm-based decision-making may affect transparency and access to these data. I will focus on the question why the transparency of the algorithms is raised at all, and what the current legal framework for the potential accessibility to them is.

scholarly journals Survey on Big Data Analytics in Public Sector of Russian Federation

2015 ◽  
Vol 55 ◽  
pp. 905-911 ◽  
Author(s):  
Kuraeva Anna ◽  
Kazantsev Nikolay
Keyword(s):  
Big Data ◽  
Public Sector ◽  
Russian Federation ◽  
Data Analytics ◽  
Big Data Analytics
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