scholarly journals Big-Data Management: A Driver for Digital Transformation?

Information ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 411
Author(s):  
Panagiotis Kostakis ◽  
Antonios Kargas
Keyword(s):  
Big Data ◽  
Data Management ◽  
Competitive Advantage ◽  
Large Volume ◽  
Rapid Evolution ◽  
Digital Transformation ◽  
Business Community ◽  
Evolution Of Technology ◽  
Global Increase ◽  
New Situation

The rapid evolution of technology has led to a global increase in data. Due to the large volume of data, a new characterization occurred in order to better describe the new situation, namel. big data. Living in the Era of Information, businesses are flooded with information through data processing. The digital age has pushed businesses towards finding a strategy to transform themselves in order to overtake market changes, successfully compete, and gain a competitive advantage. The aim of current paper is to extensively analyze the existing online literature to find the main (most valuable) components of big-data management according to researchers and the business community. Moreover, analysis was conducted to help readers in understanding how these components can be used from existing businesses during the process of digital transformation.

scholarly journals DaLiF: a data lifecycle framework for data-driven governments

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Syed Iftikhar Hussain Shah ◽  
Vassilios Peristeras ◽  
Ioannis Magnisalis
Keyword(s):  
Big Data ◽  
Data Management ◽  
Good Governance ◽  
Business Community ◽  
Data Driven ◽  
Governmental Organizations ◽  
Data Lifecycle ◽  
The Government ◽  
Data Ecosystem ◽  
Governance Transparency

AbstractThe public sector, private firms, business community, and civil society are generating data that is high in volume, veracity, velocity and comes from a diversity of sources. This kind of data is known as big data. Public Administrations (PAs) pursue big data as “new oil” and implement data-centric policies to transform data into knowledge, to promote good governance, transparency, innovative digital services, and citizens’ engagement in public policy. From the above, the Government Big Data Ecosystem (GBDE) emerges. Managing big data throughout its lifecycle becomes a challenging task for governmental organizations. Despite the vast interest in this ecosystem, appropriate big data management is still a challenge. This study intends to fill the above-mentioned gap by proposing a data lifecycle framework for data-driven governments. Through a Systematic Literature Review, we identified and analysed 76 data lifecycles models to propose a data lifecycle framework for data-driven governments (DaliF). In this way, we contribute to the ongoing discussion around big data management, which attracts researchers’ and practitioners’ interest.

Methodology for cognition of digital society

2020 ◽  
Vol 3 (2) ◽  
pp. 17-26
Author(s):  
N. N. Meshcheryakova
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Research Methods ◽  
Large Volume ◽  
Digital Transformation ◽  
Digital Society ◽  
Modern Information ◽  
Short Time

Digital sociology is a computational social science that uses modern information systems and technologies, has already formed. But the conflict with traditional sociology and its research methods has not yet been resolved. This conflict can be overcome if we remember that there is a common goal – the knowledge of the phenomena and processes of social life, which is primary in relation to the methods to be agreed upon. Digital transformation of sociology is essential, since 1) traditional sociological methods do not solve the problem of providing voluminous, reliable empirical data qualitatively and in a short time; 2) the transition from contact research methods to unobtrusive ones is in demand. The adaptation of four modern information technologies-cloud computing, big data, the Internet of things and artificial intelligence – for the purposes of sociology provides a qualitative transition in the methodology of knowledge of the digital society. Cloud computing provide researchers with tools, big data – research materials, Internet of things technology aimed at collecting indicators (receiving signals) in large volume, in real time, as direct, not indirect evidence of human behavior. The development of “artificial intelligence” technology expands the possibility of receiving processed signals of the quality of the social system without building a preliminary hypothesis, in a short time and on a large volume of processed data. Digital transformation of sociology does not mean abandoning the use of traditional methods of sociological analysis, but it involves expanding the competence of a sociologist, which requires a revision of University curricula. At the same time, combining the functions of an expert on the subject (sociologist) and data analyst in one specialist is assessed as unpromising, it is proposed to combine their professional competencies in working on unified research projects.

Exploring the Usage of Big Data Analytical Tools in Telecommunication Industry in Oman

Web Services ◽  
2019 ◽  
pp. 459-472
Author(s):  
Himyar Ali Al Jabri ◽  
Ali H. Al-Badi ◽  
Oualid Ali
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Big Data ◽  
Data Management ◽  
Competitive Advantage ◽  
Case Studies ◽  
Telecommunication Industry ◽  
A Value ◽  
Telecom Industry ◽  
Analytical Tools

Big Data has recently become a very hot topic in the field of Information Technology and Data Management. Data generated by the company's daily operations through different resources such as social media, etc. is very important because it can bring a value that will lead to a competitive advantage. The objectives of this research are to: 1) Explore the analytical tools used to manipulate Big Data in Omani telecom industry, 2) Present the benefits of using these tools, the extent of use, and the features specifically promoted these tools, and 3) Highlight the challenges/obstacles that the telecom industry in Oman facing in adopting/using Big Data analytical tools. To achieve the research objectives two case studies were conducted among the main telecom operators in Oman. This research concluded that both studied telecom operators in Oman are not ready for the DBAs. Both operators need to invest in developing the capabilities that enable them to use these tools. Once that is satisfied, then other components like the infrastructure, tools, and data can be managed very well.

scholarly journals Perception of digital transformation effect on audit quality: the case of Vietnam

2021 ◽  
Author(s):  
Anh Tran Thi Kim ◽  
Anh Hoang Ha
Keyword(s):  
Big Data ◽  
Quantitative Method ◽  
Positive Relationship ◽  
Audit Quality ◽  
Digital Transformation ◽  
Important Influence ◽  
Audit Firms ◽  
Professional Profile ◽  
Evolution Of Technology

Digital transformation has been progressively attracting attention with its important influence on accounting and auditing in recent decades. This study aims at understanding the perception of digital transformation effect on audit quality to find out the digital challenges in auditing works at all stages. This study explores the perception of the effect of digital transformation on audit quality on four aspects, which are audit users’ perception, regulations related to audit, auditors’ work, and auditors’ professional profile. A quantitative method is applied with data collected from a survey with 136 specialists in auditing. The results show a positive relationship between perception of digital transformation and audit quality. Recommendations from the findings are proposed for auditors, audit firms, and policymakers to adapt with the evolution of technology. Keywords: Digital transformation, Audit quality, Big data, AI, Blockchain

scholarly journals Characterizing Big Data Management

10.28945/2204 ◽  
2015 ◽  
Vol 12 ◽  
pp. 165-180 ◽  
Author(s):  
Rogério Rossi ◽  
Kechi Hirama
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Management ◽  
Large Volume ◽  
Process Management ◽  
Three Dimensions ◽  
Storage And Retrieval ◽  
Human Aspects ◽  
Business Approach ◽  
Support Decision Making

Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: technology, people and processes. Hence, this article discusses these dimensions: the technological dimension that is related to storage, analytics and visualization of big data; the human aspects of big data; and, in addition, the process management dimension that involves in a technological and business approach the aspects of big data management.

A Comprehensive View of Scheduling Algorithms for MapReduce Framework in Hadoop

2019 ◽  
Vol 16 (8) ◽  
pp. 3582-3586 ◽  
Author(s):  
Asha Pandian ◽  
Bharathi Varadharajulu ◽  
Albert Mayan John ◽  
Prem Jacob ◽  
Pravin
Keyword(s):  
Big Data ◽  
Data Management ◽  
Large Volume ◽  
Scheduling Algorithms ◽  
Great Difficulty ◽  
Mapreduce Framework ◽  
Important Concern ◽  
Scheduling Method ◽  
Management Techniques ◽  
Hadoop Framework

We reside in information world which makes great difficulty in quantifying the aggregate volume of information put away electronically, and exist in the unit of Zettabytes or Exabyte, hence termed as Big Data. They can be unstructured, organized or semi organized, processing of these data cannot able to be done with normal data management techniques. Hadoop framework is utilized to process huge datasets in a proficient and economical way. MapReduce system is utilized to gather information according to the solicitation. To handle expansive volume of information legitimate planning is obliged to accomplish more noteworthy execution. Scheduling jobs in parallel across the nodes is an important concern in MapReduce clusters. Also to improve the performance with the large volume of data proper scheduling method should be adopted. The objective of the work is to study about the different scheduling techniques used in Hadoop environment and to achieve effective fairness without starvation.

A Study of Big Data Analytical Frameworks in Research Data Management Using Data Mining Techniques

2021 ◽  
pp. 48-67
Author(s):  
Madhavi Arun Vaidya ◽  
Meghana Sanjeeva
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Big Data ◽  
Data Management ◽  
Large Volume ◽  
Research Data ◽  
Research Data Management ◽  
Visualization Tools ◽  
Using Data ◽  
Analytical Frameworks

Research, which is an integral part of higher education, is undergoing a metamorphosis. Researchers across disciplines are increasingly utilizing electronic tools to collect, analyze, and organize data. This “data deluge” creates a need to develop policies, infrastructures, and services in organisations, with the objective of assisting researchers in creating, collecting, manipulating, analysing, transporting, storing, and preserving datasets. Research is now conducted in the digital realm, with researchers generating and exchanging data among themselves. Research data management in context with library data could also be treated as big data without doubt due its properties of large volume, high velocity, and obvious variety. To sum up, it can be said that big datasets need to be more useful, visible, and accessible. With new and powerful analytics of big data, such as information visualization tools, researchers can look at data in new ways and mine it for information they intend to have.

Exploring the Usage of Big Data Analytical Tools in Telecommunication Industry in Oman

2017 ◽  
Vol 30 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Himyar Ali Al Jabri ◽  
Ali H. Al-Badi ◽  
Oualid Ali
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Big Data ◽  
Data Management ◽  
Competitive Advantage ◽  
Case Studies ◽  
Telecommunication Industry ◽  
A Value ◽  
Telecom Industry ◽  
Analytical Tools

Big Data has recently become a very hot topic in the field of Information Technology and Data Management. Data generated by the company's daily operations through different resources such as social media, etc. is very important because it can bring a value that will lead to a competitive advantage. The objectives of this research are to: 1) Explore the analytical tools used to manipulate Big Data in Omani telecom industry, 2) Present the benefits of using these tools, the extent of use, and the features specifically promoted these tools, and 3) Highlight the challenges/obstacles that the telecom industry in Oman facing in adopting/using Big Data analytical tools. To achieve the research objectives two case studies were conducted among the main telecom operators in Oman. This research concluded that both studied telecom operators in Oman are not ready for the DBAs. Both operators need to invest in developing the capabilities that enable them to use these tools. Once that is satisfied, then other components like the infrastructure, tools, and data can be managed very well.

HIMSS Impact18: Leading Digital Transformation und Big Data in Medicine

2018 ◽  
Vol 23 (09) ◽  
pp. 25-25
Author(s):  
Sabine Schützmann
Keyword(s):  
Big Data ◽  
Digital Transformation

Am 17. und 18. Oktober findet im Hasso-Plattner-Institut (HPI) in Potsdam zum zweiten Mal die HIMSS Impact statt: Ein englischsprachiges Symposium, welches aktuelle Trends im Gesundheitswesen, digitale Strategien und jüngste Forschungserkenntnisse beleuchtet.

The application of E-commerce among small medium enterprises : a case study in Kelantan

2007 ◽  
Vol 4 (2) ◽  
pp. 45
Author(s):  
Norudin Mansor ◽  
Che Ismail Long ◽  
Ahmad Ismail Mohd. Annuar
Keyword(s):  
Competitive Advantage ◽  
General Assumption ◽  
The State ◽  
Business Community ◽  
Research Project ◽  
Business Decision ◽  
Small Medium Enterprises ◽  
Medium Enterprises

The research project was conducted to investigate the understanding of E-commerce Application among the SMEs in the state of Kelantan. Focusing on the population of registered members of Dewan Perniagaan Melayu Malaysia, Kelantan, a total of302 respondents were selected to participate in our study. Moving in line with the general assumption of world business community it is agreed that e-commerce application is highly relevant for the survival and meeting the challenges of borderless economy. At the same time, the process of acquiring knowledge and understanding the environment, coping with changes, and speeding up the business decision, able to further enhance the competitive advantage of the SMEs. Using the established model, our investigation focused on 5 identifiable variables to demonstrate its usefulness towards motivating SMEs to adopt e-commerce. Our analysis indicated that all the selected variables were significant towards enhancing the application of e-commerce and thus maintaining competitive advantage in the industry.

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