scholarly journals Big data analytics for climate change and biodiversity in the EUBrazilCC federated cloud infrastructure

2015 ◽  
Author(s):  
Sandro Fiore ◽  
Marco Mancini ◽  
Donatello Elia ◽  
Paola Nassisi ◽  
Francisco Vilar Brasileiro ◽  
...  
Keyword(s):  
Climate Change ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cloud Infrastructure

scholarly journals Studying Cloud as IaaS for Big Data Analytics : Opportunity, Challenges

2018 ◽  
Vol 7 (2.7) ◽  
pp. 909
Author(s):  
Amitkumar Manekar ◽  
Dr Pradeepini Gera
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cloud Infrastructure ◽  
Computational Framework ◽  
New Era ◽  
Post Process ◽  
James Watt ◽  
Data Ecosystem

James Watt steam engine revolution was greatest revolution in mankind history in 20th century. In 1776, the first steam engines were installed and working in commercial enterprises. This revolution minimize and make world smaller for human being, now world is connected seamlessly. “Big Data Analytics and Cloud” these two words are second numerous revolutions in 21st century.  We are living in an era of information explosion. These two magical terms are nothing but relatively very new and fortunately diverted all market trends to a new era of computation in last decade. As these two emerging technology are their early childhood, many people were confused with its relevancy and applicability. Cloud Computing is Infrastructure based solution for managing data and computational framework. 2016 was a significantly more important year for this volumes data technology or Big Data eco system as large number of enterprises, and organizations are generating data, storing that data and worried about future aspect of that data. In 2017, corporate world take cognizance of their large volumes structured and unstructured data as these enterprises and organizations continuously generating large volumes data. The term big data doesn’t just refer to the massive amounts of data existing today, it also refers to the whole ecosystem of Storing or gathering data, Different types of data and analyzing that data. In traditional data ecosystem all leverages are with legacy system.  Transforming or migration of these traditional ecosystems to the cloud is full of great challenges and benefits. Cloud computing is an agile and scalable resource access computation paradigm, provides heterogeneous platform seamlessly with infrastructure of internet, exclusively for the trapped and work on pre and post process of big data. Now the challenges are finding opportunity and challenges for managing, migrating and abstracting cloud based big data using cloud infrastructure for future eco system of Big Data Analysis.  This paper is basically focused on this issue. We try to reevaluate the facts of existing Cloud Infrastructure as IaaS for tomorrow’s big data analytics.    

scholarly journals Big Data and Climate Change

2019 ◽  
Vol 3 (1) ◽  
pp. 12 ◽  
Author(s):  
Hossein Hassani ◽  
Xu Huang ◽  
Emmanuel Silva
Keyword(s):  
Climate Change ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Climate Science ◽  
Current Status ◽  
Future Research ◽  
Climate Data ◽  
Data Intensive ◽  
Big Data Applications

Climate science as a data-intensive subject has overwhelmingly affected by the era of big data and relevant technological revolutions. The big successes of big data analytics in diverse areas over the past decade have also prompted the expectation of big data and its efficacy on the big problem—climate change. As an emerging topic, climate change has been at the forefront of the big climate data analytics implementations and exhaustive research have been carried out covering a variety of topics. This paper aims to present an outlook of big data in climate change studies over the recent years by investigating and summarising the current status of big data applications in climate change related studies. It is also expected to serve as a one-stop reference directory for researchers and stakeholders with an overview of this trending subject at a glance, which can be useful in guiding future research and improvements in the exploitation of big climate data.

scholarly journals Intelligent Computational Techniques for Crops Yield Prediction and Fertilizer Management over Big Data Environment

2019 ◽  
Vol 8 (12) ◽  
pp. 3521-3526
Keyword(s):  
Climate Change ◽  
Big Data ◽  
Crop Yield ◽  
Precision Agriculture ◽  
Data Analytics ◽  
Seed Quality ◽  
Big Data Analytics ◽  
Computational Techniques ◽  
Yield Prediction ◽  
Crops Yield

Agriculture is one of the biggest fields to improve the economic rate of the country. Crop yield prediction is a new emerging idea in agriculture. There are several challenges of crops yield prediction in the field of precision agriculture are (i). Obtain minimized production due to climate change; (ii). Lead to different diseases; (iii). Availability of Water; (iv). No awareness of fertilizers and crop features; (v). Climate change; (vi). Unexpected weather events.Other loss factors in the agriculture are lowly seed quality, unplanned irrigation and exploitation of insecticides and fertilizers. The main aim of this research is to design the effective crop yield production and health risk analysis model by big data analytics model. Hence in this research our focus is on optimizing the significant parameters such as rainfall, temperature and fertilizers rate to obtain the P-values for testing the crop and also analyze the human health safety (farmers and suppliers) due to the dynamic change of environment and also soil nutrients. Big data analytics is the feasible platform to test and measure the crop grow in the particular agriculture field. It helps in climate, weather events prediction and also it is used to compute the sufficient resources for crop cultivation.

scholarly journals N-HyDAA - Big Data Analytics for Malaysia Climate Change Knowledge Management

10.29007/5b3v ◽  
2018 ◽  
Author(s):  
Mohammad Fikry Abdullah ◽  
Mohd Zaki Mat Amin ◽  
Mohd Fauzi Mohamad ◽  
Marini Mohamad Ideris ◽  
Zurina Zainol ◽  
...  
Keyword(s):  
Climate Change ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Economic Losses ◽  
Weather Extremes ◽  
Related Data ◽  
Water Stress Condition ◽  
Business Entities ◽  
Knowledge Portal

With the changing climate, the prognosis is that weather extremes such as floods, drought and EL Nino are likely to increase in frequency and intensity can expand billions of economic losses and effect human lives. NAHRIM Hydroclimate Data Analysis Accelerator (N-HyDAA), known as Malaysia Climate Change (CC) Knowledge Portal, the only CC knowledge portal in Malaysia primarily developed for providing CC and water-related data, information, knowledge and technologywhich is crucial for present and future water related bussines activities, engineering practices and environment. It has eight hydroclimate-environment modules, which amongst others are rainfall, floods, droughts and water stress condition using Big Data Analytics (BDA) technology by means of comprehensive analysis and interactive visualization tools. N-HyDAA is able to trace, detect, identify and visualise future water issues associated with the adverse impacts of climate change in Malaysia. N-HyDAA assist business entities, water operators, engineers, planners and decision-makers in designing, planning and developing water related program and risk management in combating climate change impact either mitigation or adaptation actions.

Big Data Analytics: The Next Big Thing

2019 ◽  
Vol 54 (5) ◽  
pp. 20
Author(s):  
Dheeraj Kumar Pradhan
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics
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