scholarly journals Utilizing big data analytics for information systems research: challenges, promises and guidelines

2016 ◽  
Vol 25 (4) ◽  
pp. 289-302 ◽  
Author(s):  
Oliver Müller ◽  
Iris Junglas ◽  
Jan vom Brocke ◽  
Stefan Debortoli
Keyword(s):  
Big Data ◽  
Information Systems ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Systems Research ◽  
Research Challenges ◽  
Information Systems Research

Big Data Analytics Adoption Factors in Improving Information Systems Security

2022 ◽  
pp. 1231-1248
Author(s):  
Marouane Balmakhtar ◽  
Scott E. Mensch
Keyword(s):  
Big Data ◽  
Information Systems ◽  
Information Security ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Review Of The Literature ◽  
Information Systems Security ◽  
Systems Security ◽  
Security Effectiveness ◽  
Research Questions

This research measured determinants that influence the willingness of IT/IA professionals to recommend Big Data analytics to improve information systems security in an organization. A review of the literature as well as the works of prior researchers provided the basis for formulation of research questions. Results of this study found that security effectiveness, organizational need, and reliability play a role in the decision to recommend big data analytics to improve information security. This research has implications for both consumers and providers of big data analytics services through the identification of factors that influence IT/IA professionals. These factors aim to improve information systems security, and therefore, which service offerings are likely to meet the needs of these professionals and their organizations.

Research Challenges in Big Data Analytics

2017 ◽  
pp. 83-99
Author(s):  
Sivamathi Chokkalingam ◽  
Vijayarani S.
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Large Scale ◽  
New Technologies ◽  
Big Data Analytics ◽  
Large Data ◽  
Data Sets ◽  
Data Types ◽  
Customer Preferences ◽  
Research Challenges

The term Big Data refers to large-scale information management and analysis technologies that exceed the capability of traditional data processing technologies. Big Data is differentiated from traditional technologies in three ways: volume, velocity and variety of data. Big data analytics is the process of analyzing large data sets which contains a variety of data types to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. Since Big Data is new emerging field, there is a need for development of new technologies and algorithms for handling big data. The main objective of this paper is to provide knowledge about various research challenges of Big Data analytics. A brief overview of various types of Big Data analytics is discussed in this paper. For each analytics, the paper describes process steps and tools. A banking application is given for each analytics. Some of research challenges and possible solutions for those challenges of big data analytics are also discussed.

Big Data Analytics Adoption Factors in Improving Information Systems Security

2019 ◽  
Vol 10 (3) ◽  
pp. 1-21
Author(s):  
Marouane Balmakhtar ◽  
Scott E. Mensch
Keyword(s):  
Big Data ◽  
Information Systems ◽  
Information Security ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Review Of The Literature ◽  
Information Systems Security ◽  
Systems Security ◽  
Security Effectiveness ◽  
Research Questions

This research measured determinants that influence the willingness of IT/IA professionals to recommend Big Data analytics to improve information systems security in an organization. A review of the literature as well as the works of prior researchers provided the basis for formulation of research questions. Results of this study found that security effectiveness, organizational need, and reliability play a role in the decision to recommend big data analytics to improve information security. This research has implications for both consumers and providers of big data analytics services through the identification of factors that influence IT/IA professionals. These factors aim to improve information systems security, and therefore, which service offerings are likely to meet the needs of these professionals and their organizations.

Research Challenges in Big Data Analytics

2016 ◽  
pp. 48-64
Author(s):  
Sivamathi Chokkalingam ◽  
Vijayarani S.
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Large Scale ◽  
New Technologies ◽  
Big Data Analytics ◽  
Large Data ◽  
Data Sets ◽  
Data Types ◽  
Customer Preferences ◽  
Research Challenges

The term Big Data refers to large-scale information management and analysis technologies that exceed the capability of traditional data processing technologies. Big Data is differentiated from traditional technologies in three ways: volume, velocity and variety of data. Big data analytics is the process of analyzing large data sets which contains a variety of data types to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. Since Big Data is new emerging field, there is a need for development of new technologies and algorithms for handling big data. The main objective of this paper is to provide knowledge about various research challenges of Big Data analytics. A brief overview of various types of Big Data analytics is discussed in this paper. For each analytics, the paper describes process steps and tools. A banking application is given for each analytics. Some of research challenges and possible solutions for those challenges of big data analytics are also discussed.

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