The impact of big data in predictive analytics towards technological development in cloud computing

2021 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Krishna Kumar Mohbey ◽  
Sunil Kumar
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Predictive Analytics ◽  
Technological Development ◽  
The Impact

Cloud Computing Big Data Adoption Impacts on Teaching and Learning in Higher Education

2022 ◽  
pp. 1719-1732
Author(s):  
Fahad Nasser Alhazmi
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Big Data ◽  
Teaching And Learning ◽  
Predictive Analytics ◽  
Qualitative Content Analysis ◽  
Research Approach ◽  
Personalised Learning ◽  
Challenges And Opportunities ◽  
The Impact

There is a rapid evolution in the purpose and value of higher education brought about by technological advancement and data ubiquity. Data mining and advanced predictive analytics are increasingly being used in higher education institutions around the world to perform tasks, ranging from student recruitment, enrolment, predicting student behaviour, and developing personalised learning schemes. This chapter evaluates and assesses the impact of big data and cloud computing in higher education. The authors adopt systematic literature research approach that employs qualitative content analysis to establish their position with regards to the impact, benefits, challenges, and opportunities of integrating big data and cloud computing to facilitate teaching and learning.

Cloud Computing Big Data Adoption Impacts on Teaching and Learning in Higher Education

2021 ◽  
pp. 53-66
Author(s):  
Fahad Nasser Alhazmi
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Big Data ◽  
Teaching And Learning ◽  
Predictive Analytics ◽  
Qualitative Content Analysis ◽  
Research Approach ◽  
Personalised Learning ◽  
Challenges And Opportunities ◽  
The Impact

There is a rapid evolution in the purpose and value of higher education brought about by technological advancement and data ubiquity. Data mining and advanced predictive analytics are increasingly being used in higher education institutions around the world to perform tasks, ranging from student recruitment, enrolment, predicting student behaviour, and developing personalised learning schemes. This chapter evaluates and assesses the impact of big data and cloud computing in higher education. The authors adopt systematic literature research approach that employs qualitative content analysis to establish their position with regards to the impact, benefits, challenges, and opportunities of integrating big data and cloud computing to facilitate teaching and learning.

scholarly journals The Impact of Big Data on Electronic Commerce in Profit Organisations in Saudi Arabia

2019 ◽  
Vol 10 (4) ◽  
pp. 106
Author(s):  
Bader A. Alyoubi
Keyword(s):  
Saudi Arabia ◽  
Big Data ◽  
Inventory Management ◽  
New Technologies ◽  
Predictive Analytics ◽  
Business Environment ◽  
Primary Data ◽  
Research Approach ◽  
Multiple Sources ◽  
The Impact

Big Data is gaining rapid popularity in e-commerce sector across the globe. There is a general consensus among experts that Saudi organisations are late in adopting new technologies. It is generally believed that the lack of research in latest technologies that are specific to Saudi Arabia that is culturally, socially, and economically different from the West, is one of the key factors for the delay in technology adoption in Saudi Arabia. Hence, to fill this gap to a certain extent and create awareness about Big Data technology, the primary goal of this research was to identify the impact of Big Data on e-commerce organisations in Saudi Arabia. Internet has changed the business environment of Saudi Arabia too. E-commerce is set for achieving new heights due to latest technological advancements. A qualitative research approach was used by conducting interviews with highly experienced professional to gather primary data. Using multiple sources of evidence, this research found out that traditional databases are not capable of handling massive data. Big Data is a promising technology that can be adopted by e-commerce companies in Saudi Arabia. Big Data’s predictive analytics will certainly help e-commerce companies to gain better insight of the consumer behaviour and thus offer customised products and services. The key finding of this research is that Big Data has a significant impact in e-commerce organisations in Saudi Arabia on various verticals like customer retention, inventory management, product customisation, and fraud detection.

scholarly journals Impact of big data and predictive analytics capability on supply chain sustainability

2018 ◽  
Vol 29 (2) ◽  
pp. 513-538 ◽  
Author(s):  
Shirish Jeble ◽  
Rameshwar Dubey ◽  
Stephen J. Childe ◽  
Thanos Papadopoulos ◽  
David Roubaud ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Theoretical Model ◽  
Performance Measures ◽  
Structural Equation ◽  
Predictive Analytics ◽  
Equation Modeling ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
The Impact

PurposeThe purpose of this paper is to develop a theoretical model to explain the impact of big data and predictive analytics (BDPA) on sustainable business development goal of the organization.Design/methodology/approachThe authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.FindingsThe statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support forH4. Although the authors did not find support forH4(moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.Originality/valueThis study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.

scholarly journals Personalization as a promise: Can Big Data change the practice of insurance?

2020 ◽  
Vol 7 (1) ◽  
pp. 205395172093514 ◽  
Author(s):  
Laurence Barry ◽  
Arthur Charpentier
Keyword(s):  
Big Data ◽  
Predictive Analytics ◽  
Special Focus ◽  
New Paradigm ◽  
Individual Level ◽  
Big Data Technologies ◽  
State Of Research ◽  
The Individual ◽  
Homogeneity Hypothesis ◽  
The Impact

The aim of this article is to assess the impact of Big Data technologies for insurance ratemaking, with a special focus on motor products.The first part shows how statistics and insurance mechanisms adopted the same aggregate viewpoint. It made visible regularities that were invisible at the individual level, further supporting the classificatory approach of insurance and the assumption that all members of a class are identical risks. The second part focuses on the reversal of perspective currently occurring in data analysis with predictive analytics, and how this conceptually contradicts the collective basis of insurance. The tremendous volume of data and the personalization promise through accurate individual prediction indeed deeply shakes the homogeneity hypothesis behind pooling. The third part attempts to assess the extent of this shift in motor insurance. Onboard devices that collect continuous driving behavioural data could import this new paradigm into these products. An examination of the current state of research on models with telematics data shows however that the epistemological leap, for now, has not happened.

scholarly journals Embracing AI and Big Data in customer journey mapping: from literature review to a theoretical framework

2019 ◽  
Vol 15 (4) ◽  
pp. 102-115 ◽  
Author(s):  
Mario D'Arco ◽  
Letizia Lo Presti ◽  
Vittoria Marino ◽  
Riccardo Resciniti
Keyword(s):  
Big Data ◽  
Predictive Analytics ◽  
Demand Forecasting ◽  
Customer Relationship ◽  
Promotion Strategy ◽  
Customer Journey ◽  
Marketing Performance ◽  
Customer Profiling ◽  
Functional Areas ◽  
The Impact

Nowadays, Big Data and Artificial Intelligence (AI) play an important role in different functional areas of marketing. Starting from this assumption, the main objective of this theoretical paper is to better understand the relationship between Big Data, AI, and customer journey mapping. For this purpose, the authors revised the extant literature on the impact of Big Data and AI on marketing practices to illustrate how such data analytics tools can increase the marketing performance and reduce the complexity of the pattern of consumer activity. The results of this research offer some interesting ideas for marketing managers. The proposed Big Data and AI framework to explore and manage the customer journey illustrates how the combined use of Big Data and AI analytics tools can offer effective support to decision-making systems and reduce the risk of bad marketing decision. Specifically, the authors suggest ten main areas of application of Big Data and AI technologies concerning the customer journey mapping. Each one supports a specific task, such as (1) customer profiling; (2) promotion strategy; (3) client acquisition; (4) ad targeting; (5) demand forecasting; (6) pricing strategy; (7) purchase history; (8) predictive analytics; (9) monitor consumer sentiments; and (10) customer relationship management (CRM) activities.

scholarly journals Analyzation and Comparison of Cloud Computing and Data Mining Techniques: Big Data and Impact of Blockchain

2021 ◽  
Vol 9 (11) ◽  
pp. 712-721
Author(s):  
Adarsh Bhandari
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Scale Up ◽  
Big Data Analytics ◽  
Multiple Sources ◽  
Huge Data ◽  
Amazon Web Services ◽  
Tools And Techniques ◽  
The Impact

Abstract: With the rapid escalation of data driven solutions, companies are integrating huge data from multiple sources in order to gain fruitful results. To handle this tremendous volume of data we need cloud based architecture to store and manage this data. Cloud computing has emerged as a significant infrastructure that promises to reduce the need for maintaining costly computing facilities by organizations and scale up the products. Even today heavy applications are deployed on cloud and managed specially at AWS eliminating the need for error prone manual operations. This paper demonstrates about certain cloud computing tools and techniques present to handle big data and processes involved while extracting this data till model deployment and also distinction among their usage. It will also demonstrate, how big data analytics and cloud computing will change methods that will later drive the industry. Additionally, a study is presented later in the paper about management of blockchain generated big data on cloud and making analytical decision. Furthermore, the impact of blockchain in cloud computing and big data analytics has been employed in this paper. Keywords: Cloud Computing, Big Data, Amazon Web Services (AWS), Google Cloud Platform (GCP), SaaS, PaaS, IaaS.

scholarly journals Construction of Live Broadcast Training Platform Based on “Cloud Computing” and “Big Data” and “Wireless Communication Technology”

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Zhidong Sun ◽  
Xueqing Li
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Wireless Communication ◽  
Communication Technology ◽  
Security Policy ◽  
High Efficiency ◽  
Rapid Development ◽  
Science And Technology ◽  
Live Broadcast ◽  
The Impact

With the rapid development of information technology, a scientific theory is brought by the rapid progress of science and technology. The advancement of science and technology of the impact on every field, changing the mode of transmission of information, the advent of big data for promotion and dissemination of resources played their part, let more and more people benefit. In the context of cloud computing, big data ushered in another upsurge of development and growth. Given this, the live broadcast training platform, which focuses on enterprise staff training and network education, arises at the right moment. People favor its convenience, real-time performance, and high efficiency. However, the low-value density of big data and cloud computing’s security problem has difficulties constructing a live broadcast training platform. In this paper, the live broadcast training platform’s structure is improved by constructing three modules: the live training module based on cloud computing, the user recommendation module based on big data, and the security policy guarantee module. In addition, to ensure that the trainees can receive training anytime and anywhere, this paper uses wireless communication technology to ensure the quality and speed of all users’ live video sources.

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