Big Data Analytics and Models

2022 ◽  
pp. 164-187
Author(s):  
Ferdi Sönmez ◽  
Ziya Nazım Perdahçı ◽  
Mehmet Nafiz Aydın
Keyword(s):  
Big Data ◽  
Important Implication ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Financial Econometrics ◽  
Optimization Models ◽  
Modern World ◽  
Financial Instability ◽  
The Future ◽  
Social Environmental

When uncertainty is regarded as a surprise and an event in the minds, it can be said that individuals can change the future view. Market, financial, operational, social, environmental, institutional and humanitarian risks and uncertainties are the inherent realities of the modern world. Life is suffused with randomness and volatility; everything momentous that occurs in the illustrious sweep of history, or in our individual lives, is an outcome of uncertainty. An important implication of such uncertainty is the financial instability engendered to the victims of different sorts of perils. This chapter is intended to explore big data analytics as a comprehensive technique for processing large amounts of data to uncover insights. Several techniques before big data analytics like financial econometrics and optimization models have been used. Therefore, initially these techniques are mentioned. Then, how big data analytics has altered the methods of analysis is mentioned. Lastly, cases promoting big data analytics are mentioned.

Big Data Analytics and Models

2020 ◽  
pp. 10-33
Author(s):  
Ferdi Sönmez ◽  
Ziya Nazım Perdahçı ◽  
Mehmet Nafiz Aydın
Keyword(s):  
Big Data ◽  
Important Implication ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Financial Econometrics ◽  
Optimization Models ◽  
Modern World ◽  
Financial Instability ◽  
The Future ◽  
Social Environmental

When uncertainty is regarded as a surprise and an event in the minds, it can be said that individuals can change the future view. Market, financial, operational, social, environmental, institutional and humanitarian risks and uncertainties are the inherent realities of the modern world. Life is suffused with randomness and volatility; everything momentous that occurs in the illustrious sweep of history, or in our individual lives, is an outcome of uncertainty. An important implication of such uncertainty is the financial instability engendered to the victims of different sorts of perils. This chapter is intended to explore big data analytics as a comprehensive technique for processing large amounts of data to uncover insights. Several techniques before big data analytics like financial econometrics and optimization models have been used. Therefore, initially these techniques are mentioned. Then, how big data analytics has altered the methods of analysis is mentioned. Lastly, cases promoting big data analytics are mentioned.

scholarly journals A functional framework based on big data analytics for smart farming

2021 ◽  
Vol 24 (3) ◽  
pp. 1772
Author(s):  
Loubna Rabhi ◽  
Noureddine Falih ◽  
Lekbir Afraites ◽  
Belaid Bouikhalene
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
New Products ◽  
Big Data Analytics ◽  
Decision Making Process ◽  
Time Production ◽  
Smart Farming ◽  
The Future

Big <span>data in agriculture is defined as massive volumes of data with a wide variety of sources and types which can be captured using internet of things sensors (soil and crops sensors, drones, and meteorological stations), analyzed and used for decision-making. In the era of internet of things (IoT) tools, connected agriculture has appeared. Big data outputs can be exploited by the future connected agriculture in order to reduce cost and time production, improve yield, develop new products, offer optimization and smart decision-making. In this article, we propose a functional framework to model the decision-making process in digital and connected agriculture</span>.

scholarly journals Significance of Technology and Digital Transformation in Shaping the Future of Oil and Gas Industry

2021 ◽  
Vol 12 (3) ◽  
pp. 3345-3352
Author(s):  
Shubham Parsoya Et.al
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Oil And Gas ◽  
Big Data Analytics ◽  
Oil And Gas Industry ◽  
Digital Transformation ◽  
Gas Industry ◽  
The Future

Digital transformation in the field of oil and Gas industry is already a significant impact creator. It is actually act like catalyst through which the overall functionality of the oil and gas industry get enhanced and the overall output with the help of technologically-advanced mechanism, increased up to manifold. In the present scenario, the over-all quest is not just about the volume of the oil and petroleum, but it is also regarding the overall value generated throughout the process. And such enhanced level of value generation is taking place with great pace with the help of enhanced level of implementations of different types of technologies in different type of activities related to the oil and gas industry. In the present scenario, oil and gas industry’s business model is no longer depending upon just the inflated and narrow based value-chain mechanism. It is actually depending upon the almost all modernized and futuristic technologies. The modern technologies include big data analytics, 3D printing technology, cyber security, digital marketing, Artificial Intelligence, Internet of Things, drone technologies, database management system, etc. all these technologies are not only supports in handling the overall business capability of the oil and Gas Industries, but also eliminate the overall negative impact generating elements. With the help of technologies and digital transformation, the overall profitability of the oil and gas industry enhanced. Digital transformation is a prominent and significant impact creator which is not limited to the oil and gas industry, but also reaching up to the all-global level Businesses. It is transforming the overall business operations by enhancing the speed of innovation and making the use of practical knowledge base which ultimately enhance the overall power of operations and increase efficiencies. With the emergence of digital transformation technologies especially with the emergence of big data analytics, the Internet of Things and Artificial Intelligence have supports several types of innovative and new ways of developing and transforming the overall market as well as the customer satisfaction in significant manner. All such innovative technologies and digital transformations are contributing significantly in shaping the future of oil and gas industry

scholarly journals The Hype of Big Data Analytics and Auditors

2019 ◽  
Vol 8 (2) ◽  
pp. 1-4 ◽  
Author(s):  
Prem Lal Joshi ◽  
Govindan Marthandan
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Business Models ◽  
Big Data Analytics ◽  
Cognitive Tasks ◽  
Fast Tracking ◽  
The Future

In the era of fast-tracking digitization and unconventional big data analytics, business models are being reshaped and they impact auditing amongst auditors. This viewpoint paper takes into account the procedures underlying on big data and its analytics in driving the evolution of business and identifies some of the unresolved issues and concerns on auditors, especially in the context of cognitive tasks. The paper continues to focus on the current spate of discussions on big data and auditing profession. It explains the nature of big data and its characteristics as well as the output types. This paper also tries to find answers for what is new in it, how it assists the auditors along with some unresolved  issues and concerns. Since big data analytics is the future, auditors need to reshape themselves in terms of skills and competencies to meet the emerging technological challenges. 

Modern Statistical Modeling in Machine Learning and Big Data Analytics

2020 ◽  
pp. 135-151
Author(s):  
Niloofar Ramezani
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Statistical Modeling ◽  
Statistical Models ◽  
Data Analytics ◽  
High Dimensional Data ◽  
Big Data Analytics ◽  
High Dimensional ◽  
Statistical Techniques ◽  
The Future

Machine learning, big data, and high dimensional data are the topics we hear about frequently these days, and some even call them the wave of the future. Therefore, it is important to use appropriate statistical models, which have been established for many years, and their efficiency has already been evaluated to contribute into advancing machine learning, which is a relatively newer field of study. Different algorithms that can be used within machine learning, depending on the nature of the variables, are discussed, and appropriate statistical techniques for modeling them are presented in this chapter.

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