Forecasting the Trends in Cloud Computing and its Impact on Future IT Business

2015 ◽  
pp. 2354-2372
Author(s):  
Ebin Deni Raj ◽  
L. D. Dhinesh Babu ◽  
Ezendu Ariwa ◽  
M. Nirmala ◽  
P. Venkata Krishna
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Business Processes ◽  
Big Data Analytics ◽  
Literature Survey ◽  
Mobile Cloud ◽  
Business Impact ◽  
Current Trends ◽  
To Come ◽  
Almost All

Cloud computing has become the cutting-edge technology for information technology processing and high-end computational tasks. Cloud has started playing its part in almost all business processes. Big data in cloud has become the buzzword. The business impact of cloud has deepened with the growth of big data analytics. Current trends such as green cloud computing, mobile cloud computing, and big data have created social as well as business impact. In this chapter, the authors analyze the field of cloud computing and perform an intense literature survey augmented with mathematical analysis. The forecast on the future of cloud and analysis of the current trends shows that cloud computing is a promising technology that will evolve further in years to come.

Forecasting the Trends in Cloud Computing and its Impact on Future IT Business

2014 ◽  
pp. 14-32 ◽  
Author(s):  
Ebin Deni Raj ◽  
L. D. Dhinesh Babu ◽  
EzenduAriwa ◽  
M. Nirmala ◽  
P. Venkata Krishna
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Business Processes ◽  
Big Data Analytics ◽  
Literature Survey ◽  
Mobile Cloud ◽  
Business Impact ◽  
Current Trends ◽  
To Come ◽  
Almost All

Cloud computing has become the cutting-edge technology for information technology processing and high-end computational tasks. Cloud has started playing its part in almost all business processes. Big data in cloud has become the buzzword. The business impact of cloud has deepened with the growth of big data analytics. Current trends such as green cloud computing, mobile cloud computing, and big data have created social as well as business impact. In this chapter, the authors analyze the field of cloud computing and perform an intense literature survey augmented with mathematical analysis. The forecast on the future of cloud and analysis of the current trends shows that cloud computing is a promising technology that will evolve further in years to come.

scholarly journals Automation of Big Data Analytics Using Robotic Process Automation

2021 ◽  
pp. 602-605
Author(s):  
G. Malini
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Business Processes ◽  
Big Data Analytics ◽  
Human Interaction ◽  
Process Automation ◽  
Raw Data ◽  
Robotic Process Automation ◽  
Manual Intervention ◽  
Almost All

Robotic Process Automation (RPA) is now becomes a buzzword and makes it mark on almost all fields in assisting automation of repetitive human intensive tasks in a simpler manner. RPA is nothing but a software solution that mimics the human interaction with computing software and applications without manual intervention. RPA has already been adapted in almost every business processes which are repetitive. As we are in the age of information the need for retrieval of patterns from raw data is increasing unimaginably so the needs for effective tools are also in a greater need. The effectiveness of RPA can be incorporated into the ever growing data analytics to automate the process of finding patterns and predictions from big data.

Trends and Opportunities in Health Analytics as a Service and Implications for Use in Low Resource Settings: A Literature Review Abstract (Preprint)

2019 ◽  
Author(s):  
Meghana Bastwadkar ◽  
Carolyn McGregor ◽  
S Balaji
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Intensive Care ◽  
Literature Review ◽  
Health Monitoring ◽  
Data Analytics ◽  
Neonatal Intensive Care ◽  
Big Data Analytics ◽  
Healthcare Facilities

BACKGROUND This paper presents a systematic literature review of existing remote health monitoring systems with special reference to neonatal intensive care (NICU). Articles on NICU clinical decision support systems (CDSSs) which used cloud computing and big data analytics were surveyed. OBJECTIVE The aim of this study is to review technologies used to provide NICU CDSS. The literature review highlights the gaps within frameworks providing HAaaS paradigm for big data analytics METHODS Literature searches were performed in Google Scholar, IEEE Digital Library, JMIR Medical Informatics, JMIR Human Factors and JMIR mHealth and only English articles published on and after 2015 were included. The overall search strategy was to retrieve articles that included terms that were related to “health analytics” and “as a service” or “internet of things” / ”IoT” and “neonatal intensive care unit” / ”NICU”. Title and abstracts were reviewed to assess relevance. RESULTS In total, 17 full papers met all criteria and were selected for full review. Results showed that in most cases bedside medical devices like pulse oximeters have been used as the sensor device. Results revealed a great diversity in data acquisition techniques used however in most cases the same physiological data (heart rate, respiratory rate, blood pressure, blood oxygen saturation) was acquired. Results obtained have shown that in most cases data analytics involved data mining classification techniques, fuzzy logic-NICU decision support systems (DSS) etc where as big data analytics involving Artemis cloud data analysis have used CRISP-TDM and STDM temporal data mining technique to support clinical research studies. In most scenarios both real-time and retrospective analytics have been performed. Results reveal that most of the research study has been performed within small and medium sized urban hospitals so there is wide scope for research within rural and remote hospitals with NICU set ups. Results have shown creating a HAaaS approach where data acquisition and data analytics are not tightly coupled remains an open research area. Reviewed articles have described architecture and base technologies for neonatal health monitoring with an IoT approach. CONCLUSIONS The current work supports implementation of the expanded Artemis cloud as a commercial offering to healthcare facilities in Canada and worldwide to provide cloud computing services to critical care. However, no work till date has been completed for low resource setting environment within healthcare facilities in India which results in scope for research. It is observed that all the big data analytics frameworks which have been reviewed in this study have tight coupling of components within the framework, so there is a need for a framework with functional decoupling of components.

Application of Big Data Analytics via Cloud Computing

2016 ◽  
Author(s):  
Yunus Yetis ◽  
Ruthvik Goud Sara ◽  
Berat A. Erol ◽  
Halid Kaplan ◽  
Abdurrahman Akuzum ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics

scholarly journals Big Data using Cloud Computing - Opportunities for Small and Medium-sized Enterprises

2016 ◽  
Vol 4 (1) ◽  
pp. 129 ◽  
Author(s):  
Narasimha Rao Vajjhala ◽  
Ervin Ramollari
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Fault Tolerance ◽  
Competitive Advantage ◽  
Computer Architecture ◽  
Financial Resources ◽  
Future Research ◽  
Current Trends ◽  
Low Performance ◽  
Research Frontiers

Big Data has been listed as one of the current and future research frontiers by Gartner. Large-sized companies are already investing on and leveraging big data. Small-sized and medium-sized enterprises (SMEs) can also leverage big data to gain a strategic competitive advantage but are often limited by the lack of adequate financial resources to invest on the technology and manpower. Several big data challenges still exist especially in computer architecture that is CPU-heavy but I/O poor. Cloud computing eliminates the need to maintain expensive computing hardware and software. Cloud computing resources and techniques can be leveraged to address the traditional problems associated with fault tolerance and low performance causing bottlenecks to using big data. SMEs can take advantage of cloud computing techniques to avail the advantages of big data without significant investments in technology and manpower. This paper explores the current trends in the area of big data using cloud resources and how SMEs can take advantage of these technological trends. The results of this study will benefit SMEs in identifying and exploring possible opportunities and also understanding the challenges in leveraging big data.

scholarly journals The Smart Triad : Big Data Analytics , Cloud Computing and Internet of Things to shape the Smart Home, Smart City, Smart Business & Smart Country

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3594-3600 ◽  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Smart Home ◽  
Service Providers ◽  
Irrigation System ◽  
Electronic Devices ◽  
Big Data Analytics ◽  
User Privacy

Big data analytics, cloud computing & internet of things are a smart triad which have started shaping our future towards smart home, city, business, country. Internet of things is a convergence of intelligent networks, electronic devices, and cloud computing. The source of big data at different connected electronic devices is stored on cloud server for analytics. Cloud provides the readymade infrastructure, remote processing power to consumers of internet of things. Cloud computing also gives device manufacturers and service providers access to ―advanced analytics and monitoring‖, ―communication between services and devices‖, ―user privacy and security‖. This paper, presents an overview of internet of things, role of cloud computing & big data analytics towards IoT. In this paper IoT enabled automatic irrigation system is proposed that saves data over ―ThingSpeak‖ database an IoT analytics platform through ESP8266 wifi module. This paper also summarizes the application areas and discusses the challenges of IoT.

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