Advertisement
| emerging technologies in data analytics: Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics Taser, Pelin Yildirim, 2021-11-05 The internet of things (IoT) has emerged to address the need for connectivity and seamless integration with other devices as well as big data platforms for analytics. However, there are challenges that IoT-based applications face including design and implementation issues; connectivity problems; data gathering, storing, and analyzing in cloud-based environments; and IoT security and privacy issues. Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics is a critical reference source that provides theoretical frameworks and research findings on IoT and big data integration. Highlighting topics that include wearable sensors, machine learning, machine intelligence, and mobile computing, this book serves professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. It is therefore of most value to data scientists, computer scientists, data analysts, IT specialists, academicians, professionals, researchers, and students working in the field of information and knowledge management in various disciplines that include but are not limited to information and communication sciences, administrative sciences and management, education, sociology, computer science, etc. Moreover, the book provides insights and supports executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments. |
| emerging technologies in data analytics: Challenges and Applications of Data Analytics in Social Perspectives Sathiyamoorthi, V., Elci, Atilla, 2020-12-04 With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress. Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students. |
| emerging technologies in data analytics: Microservices in Big Data Analytics Anil Chaudhary, Chothmal Choudhary, Mukesh Kumar Gupta, Chhagan Lal, Tapas Badal, 2019-11-26 These proceedings gather cutting-edge papers exploring the principles, techniques, and applications of Microservices in Big Data Analytics. The ICETCE-2019 is the latest installment in a successful series of annual conferences that began in 2011. Every year since, it has significantly contributed to the research community in the form of numerous high-quality research papers. This year, the conference’s focus was on the highly relevant area of Microservices in Big Data Analytics. |
| emerging technologies in data analytics: Emerging Technologies and Applications in Data Processing and Management Ma, Zongmin, Yan, Li, 2019-06-28 Advances in web technology and the proliferation of sensors and mobile devices connected to the internet have resulted in the generation of immense data sets available on the web that need to be represented, saved, and exchanged. Massive data can be managed effectively and efficiently to support various problem-solving and decision-making techniques. Emerging Technologies and Applications in Data Processing and Management is a critical scholarly publication that examines the importance of data management strategies that coincide with advancements in web technologies. Highlighting topics such as geospatial coverages, data analysis, and keyword query, this book is ideal for professionals, researchers, academicians, data analysts, web developers, and web engineers. |
| emerging technologies in data analytics: Big Data, Big Analytics Michael Minelli, Michele Chambers, Ambiga Dhiraj, 2013-01-22 Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more. |
| emerging technologies in data analytics: Emerging Technology and Architecture for Big-data Analytics Anupam Chattopadhyay, Chip Hong Chang, Hao Yu, 2017-04-19 This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The presentation is designed to be accessible to a broad audience, with general knowledge of hardware design and some interest in big-data analytics. Coverage includes emerging technology and devices for data-analytics, circuit design for data-analytics, and architecture and algorithms to support data-analytics. Readers will benefit from the realistic context used by the authors, which demonstrates what works, what doesn’t work, and what are the fundamental problems, solutions, upcoming challenges and opportunities. Provides a single-source reference to hardware architectures for big-data analytics; Covers various levels of big-data analytics hardware design abstraction and flow, from device, to circuits and systems; Demonstrates how non-volatile memory (NVM) based hardware platforms can be a viable solution to existing challenges in hardware architecture for big-data analytics. |
| emerging technologies in data analytics: Emerging Technologies in Computer Engineering: Microservices in Big Data Analytics Arun K. Somani, Seeram Ramakrishna, Anil Chaudhary, Chothmal Choudhary, Basant Agarwal, 2019-05-17 This book constitutes the refereed proceedings of the Second International Conference on Emerging Technologies in Computer Engineering: Microservices in Big Data Analytics, ICETCE 2019, held in Jaipur, India, in February 2019. The 28 revised full papers along with 1 short paper presented were carefully reviewed and selected from 253 submissions. ICETCE conference aims to showcase advanced technologies, techniques, innovations and equipments in computer engineering. It provides a platform for researchers, scholars, experts, technicians, government officials and industry personnel from all over the world to discuss and share their valuable ideas and experiences. |
| emerging technologies in data analytics: Objets persans. Argenteries. Miniatures... Objets de la Chine et du Japon, céramiques, Sculptures. Meubles , 1927 |
| emerging technologies in data analytics: Implementing Data Analytics and Architectures for Next Generation Wireless Communications Bhatt, Chintan, Kumar, Neeraj, Bashir, Ali Kashif, Alazab, Mamoun, 2021-08-13 Wireless communication is continuously evolving to improve and be a part of our daily communication. This leads to improved quality of services and applications supported by networking technologies. We are now able to use LTE, LTE-Advanced, and other emerging technologies due to the enormous efforts that are made to improve the quality of service in cellular networks. As the future of networking is uncertain, the use of deep learning and big data analytics is a point of focus as it can work in many capacities at a variety of levels for wireless communications. Implementing Data Analytics and Architectures for Next Generation Wireless Communications addresses the existing and emerging theoretical and practical challenges in the design, development, and implementation of big data algorithms, protocols, architectures, and applications for next generation wireless communications and their applications in smart cities. The chapters of this book bring together academics and industrial practitioners to exchange, discuss, and implement the latest innovations and applications of data analytics in advanced networks. Specific topics covered include key encryption techniques, smart home appliances, fog communication networks, and security in the internet of things. This book is valuable for technologists, data analysts, networking experts, practitioners, researchers, academicians, and students. |
| emerging technologies in data analytics: Data Science and Emerging Technologies Yap Bee Wah, Michael W. Berry, Azlinah Mohamed, Dhiya Al-Jumeily, 2023-03-31 The book presents selected papers from International Conference on Data Science and Emerging Technologies (DaSET 2022), held online at UNITAR International University, Malaysia, during December 20–21, 2022. This book aims to present current research and applications of data science and emerging technologies. The deployment of data science and emerging technology contributes to the achievement of the Sustainable Development Goals for social inclusion, environmental sustainability, and economic prosperity. Data science and emerging technologies such as artificial intelligence and blockchain are useful for various domains such as marketing, health care, finance, banking, environmental, and agriculture. An important grand challenge in data science is to determine how developments in computational and social-behavioral sciences can be combined to improve well-being, emergency response, sustainability, and civic engagement in a well-informed, data-driven society. The topics of this book include, but not limited to: artificial intelligence, big data technology, machine and deep learning, data mining, optimization algorithms, blockchain, Internet of Things (IoT), cloud computing, computer vision, cybersecurity, augmented and virtual reality, cryptography, and statistical learning. |
| emerging technologies in data analytics: Learning to Love Data Science Mike Barlow, 2015 Until recently, many people thought big data was a passing fad. Data science was an enigmatic term. Today, big data is taken seriously, and data science is considered downright sexy. With this anthology of reports from award-winning journalist Mike Barlow, you'll appreciate how data science is fundamentally altering our world, for better and for worse. Barlow paints a picture of the emerging data space in broad strokes. From new techniques and tools to the use of data for social good, you'll find out how far data science reaches. With this anthology, you'll learn how: Analysts can now get results from their data queries in near real time Indie manufacturers are blurring the lines between hardware and software Companies try to balance their desire for rapid innovation with the need to tighten data security Advanced analytics and low-cost sensors are transforming equipment maintenance from a cost center to a profit center CIOs have gradually evolved from order takers to business innovators New analytics tools let businesses go beyond data analysis and straight to decision-making Mike Barlow is an award-winning journalist, author, and communications strategy consultant. Since launching his own firm, Cumulus Partners, he has represented major organizations in a number of industries. |
| emerging technologies in data analytics: Emerging Technologies in Data Mining and Information Security Ajith Abraham, Paramartha Dutta, Jyotsna Kumar Mandal, Abhishek Bhattacharya, Soumi Dutta, 2018-09-01 The book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Management, Kolkata, India, on February 23–25, 2018. It comprises high-quality research by academics and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, case studies related to all the areas of data mining, machine learning, IoT and information security. |
| emerging technologies in data analytics: New Technologies for Human Rights Law and Practice Molly K. Land, Jay D. Aronson, 2018-04-19 New technological innovations offer significant opportunities to promote and protect human rights. At the same time, they also pose undeniable risks. In some areas, they may even be changing what we mean by human rights. The fact that new technologies are often privately controlled raises further questions about accountability and transparency and the role of human rights in regulating these actors. This volume - edited by Molly K. Land and Jay D. Aronson - provides an essential roadmap for understanding the relationship between technology and human rights law and practice. It offers cutting-edge analysis and practical strategies in contexts as diverse as autonomous lethal weapons, climate change technology, the Internet and social media, and water meters. This title is also available as Open Access. |
| emerging technologies in data analytics: The Emerging Technology of Big Data Heru Susanto, Fang-Yie Leu, Chin Kang Chen, 2019-03-29 Big Data is now highly regarded and accepted as a useful tool to help organizations manage their data and information effectively and efficiently. This new volume, The Emerging Technology of Big Data: Its Impact as a Tool for ICT Development, looks at the new technology that has emerged to meet the growing need and demand and studies the impact of Big Data in several areas of today’s society, including social media, business process re-engineering, science, e-learning, higher education, business intelligence, and green computing. In today’s modern society, information system (IS) through Big Data contributes to the success of organizations because it provides a solid foundation for increasing both efficiency and productivity. Many business organizations and educational institutions realize that compliance with Big Data will affect their prospects for success. Everyday, the amount of data collected from digital tools grows tremendously. As the amount of data increases, the use of IS becomes more and more essential. The book looks at how large datasets and analytics have slowly crept into the world of education and discusses methods of teaching and learning and the collection of student-learning data. The final chapter of the book considers the environmental impacts of ICT and emphasizes green ICT awareness as a corporate strategy through information systems. The global ICT industry accounts for approximately 2 percent of global carbon dioxide (CO2) emissions, and the manufacture, shipping, and disposal of ICT equipment also contributes environmentally. This chapter addresses these issues. The information provided here will be valuable information for education professionals, businesses, faculty, scientists and researchers, and others. |
| emerging technologies in data analytics: Handbook of Data Science Approaches for Biomedical Engineering Valentina Emilia Balas, Vijender Kumar Solanki, Manju Khari, Raghvendra Kumar, 2019-11-13 Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. - Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things - Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things - Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more |
| emerging technologies in data analytics: Real-Time Big Data Analytics: Emerging Architecture Mike Barlow, 2013-06-24 Five or six years ago, analysts working with big datasets made queries and got the results back overnight. The data world was revolutionized a few years ago when Hadoop and other tools made it possible to getthe results from queries in minutes. But the revolution continues. Analysts now demand sub-second, near real-time query results. Fortunately, we have the tools to deliver them. This report examines tools and technologies that are driving real-time big data analytics. |
| emerging technologies in data analytics: Emerging Technologies in Computing Pramod Kumar, Anuradha Tomar, R. Sharmila, 2021-12-20 Emerging Technologies in Computing: Theory, Practice, and Advances reviews the past, current, and future needs of technologies in the computer science field while it also discusses the emerging importance of appropriate practices, advances, and their impact. It outlines emerging technologies and their principles, challenges, and applications as well as issues involved in the digital age. With the rapid development of technologies, it becomes increasingly important for us to remain up to date on new and emerging technologies. It draws a clear illustration for all those who have a strong interest in emerging computing technologies and their impacts on society. Features: Includes high-quality research work by academicians and industrial experts in the field of computing Offers case studies related to Artificial Intelligence, Blockchain, Internet of Things, Multimedia Big Data, Blockchain, Augmented Reality, Data Science, Robotics, Cybersecurity, 3D Printing, Voice Assistants and Chatbots, and Future Communication Networks Serves as a valuable reference guide for anyone seeking knowledge about where future computing is heading |
| emerging technologies in data analytics: Emerging Technologies in Computing Mahdi H. Miraz, Peter S. Excell, Andrew Ware, Safeeullah Soomro, Maaruf Ali, 2020-09-28 This book constitutes the refereed conference proceedings of the Third International Conference on Emerging Technologies in Computing, iCEtiC 2020, held in London, UK, in August 2020. Due to VOVID-19 pandemic the conference was helt virtually.The 25 revised full papers were reviewed and selected from 65 submissions and are organized in topical sections covering blockchain and cloud computing; security, wireless sensor networks and IoT; AI, big data and data analytics; emerging technologies in engineering, education and sustainable development. |
| emerging technologies in data analytics: Applications of Machine Learning in Big-Data Analytics and Cloud Computing Subhendu Kumar Pani, Somanath Tripathy, George Jandieri, Sumit Kundu, Talal Ashraf Butt, 2022-09-01 Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics. |
| emerging technologies in data analytics: Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing Velayutham, Sathiyamoorthi, 2021-01-29 In today’s market, emerging technologies are continually assisting in common workplace practices as companies and organizations search for innovative ways to solve modern issues that arise. Prevalent applications including internet of things, big data, and cloud computing all have noteworthy benefits, but issues remain when separately integrating them into the professional practices. Significant research is needed on converging these systems and leveraging each of their advantages in order to find solutions to real-time problems that still exist. Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing is a pivotal reference source that provides vital research on the relation between these technologies and the impact they collectively have in solving real-world challenges. While highlighting topics such as cloud-based analytics, intelligent algorithms, and information security, this publication explores current issues that remain when attempting to implement these systems as well as the specific applications IoT, big data, and cloud computing have in various professional sectors. This book is ideally designed for academicians, researchers, developers, computer scientists, IT professionals, practitioners, scholars, students, and engineers seeking research on the integration of emerging technologies to solve modern societal issues. |
| emerging technologies in data analytics: Artificial Intelligence, Machine Learning, and Data Science Technologies Neeraj Mohan, Ruchi Singla, Priyanka Kaushal, Seifedine Kadry, 2021-10-11 This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science. |
| emerging technologies in data analytics: Emerging Technologies in Data Mining and Information Security Paramartha Dutta, Satyajit Chakrabarti, Abhishek Bhattacharya, Soumi Dutta, Vincenzo Piuri, 2022-09-28 This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2022) held at Institute of Engineering & Management, Kolkata, India, during February 23–25, 2022. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers and case studies related to all the areas of data mining, machine learning, Internet of Things (IoT) and information security. |
| emerging technologies in data analytics: Application of Big Data for National Security Babak Akhgar, Gregory B. Saathoff, Hamid R Arabnia, Richard Hill, Andrew Staniforth, Petra Saskia Bayerl, 2015-02-14 Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national security, and law, as well as computer sciences, criminology, linguistics, and psychology, creating a unique cross-disciplinary collection of knowledge and insights into this increasingly global issue. The strategic frameworks and critical factors presented in Application of Big Data for National Security consider technical, legal, ethical, and societal impacts, but also practical considerations of Big Data system design and deployment, illustrating how data and security concerns intersect. In identifying current and future technical and operational challenges it supports law enforcement and government agencies in their operational, tactical and strategic decisions when employing Big Data for national security - Contextualizes the Big Data concept and how it relates to national security and crime detection and prevention - Presents strategic approaches for the design, adoption, and deployment of Big Data technologies in preventing terrorism and reducing crime - Includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context - Indicates future directions for Big Data as an enabler of advanced crime prevention and detection |
| emerging technologies in data analytics: Handbook of Research on Advances in Data Analytics and Complex Communication Networks P. Venkata Krishna, 2021 This edited book discusses data analytics and complex communication networks and recommends new methodologies, system architectures, and other solutions to prevail over the current limitations faced by the field-- |
| emerging technologies in data analytics: Emerging Technologies in Data Mining and Information Security João Manuel R. S. Tavares, Satyajit Chakrabarti, Abhishek Bhattacharya, Sujata Ghatak, 2021-05-04 This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020) held at the University of Engineering & Management, Kolkata, India, during July 2020. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of things (IoT), and information security. |
| emerging technologies in data analytics: Data Science and Emerging Technologies Yap Bee Wah, Dhiya Al-Jumeily Obe, Michael W. Berry, 2024-04-14 The book presents selected papers from International Conference on Data Science and Emerging Technologies (DaSET 2023), held online at UNITAR International University, Malaysia during December 4–5, 2023. This book presents current research and applications of data science and emerging technologies. The topics covered are artificial intelligence, big data technology, machine and deep learning, data mining, optimization algorithms, blockchain, Internet of Things (IoT), cloud computing, computer vision, cybersecurity, augmented and virtual reality, cryptography, and statistical learning. |
| emerging technologies in data analytics: The Organisation of Tomorrow Mark Van Rijmenam, 2019-07-19 The Organisation of Tomorrow presents a new model of doing business and explains how big data analytics, blockchain and artificial intelligence force us to rethink existing business models and develop organisations that will be ready for human-machine interactions. It also asks us to consider the impacts of these emerging information technologies on people and society. Big data analytics empowers consumers and employees. This can result in an open strategy and a better understanding of the changing environment. Blockchain enables peer-to-peer collaboration and trustless interactions governed by cryptography and smart contracts. Meanwhile, artificial intelligence allows for new and different levels of intensity and involvement among human and artificial actors. With that, new modes of organising are emerging: where technology facilitates collaboration between stakeholders; and where human-to-human interactions are increasingly replaced with human-to-machine and even machine-to-machine interactions. This book offers dozens of examples of industry leaders such as Walmart, Telstra, Alibaba, Microsoft and T-Mobile, before presenting the D2 + A2 model – a new model to help organisations datafy their business, distribute their data, analyse it for insights and automate processes and customer touchpoints to be ready for the data-driven and exponentially-changing society that is upon us This book offers governments, professional services, manufacturing, finance, retail and other industries a clear approach for how to develop products and services that are ready for the twenty-first century. It is a must-read for every organisation that wants to remain competitive in our fast-changing world. |
| emerging technologies in data analytics: Emerging Technologies in Computing Mahdi H. Miraz, Peter Excell, Andrew Ware, Safeeullah Soomro, Maaruf Ali, 2018-07-20 This book constitutes the refereed conference proceedings of the First International Conference on Emerging Technologies in Computing, iCEtiC 2018, held in London, UK, in August 2018. The 26 revised full papers were reviewed and selected from more than 59 submissions and are organized in topical sections covering Cloud, IoT and distributed computing, software engineering, communications engineering and vehicular technology, AI, expert systems and big data analytics, Web information systems and applications, security, database system, economics and business engineering, mLearning and eLearning. |
| emerging technologies in data analytics: Emerging Technologies for Smart Cities Prabin K. Bora, Sukumar Nandi, Shakuntala Laskar, 2021-06-11 This book comprises the select proceedings of the International Conference on Emerging Global Trends in Engineering and Technology (EGTET 2020), held in Guwahati, India. The chapters in this book focus on the latest cleaner, greener, and efficient technologies being developed for the implementation of smart cities across the world. The broader topical sections include Smart Buildings, Infrastructures and Disaster Management; Smart Governance; Technologies for Smart Cities, and Wireless Connectivity for Smart Cities. This book will cater to students, researchers, industry professionals, and policy making bodies interested and involved in the planning and implementation of smart city projects. |
| emerging technologies in data analytics: Industrial IoT Technologies and Applications Jiafu Wan, Iztok Humar, Daqiang Zhang, 2016-08-17 This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Industrial IoT Technologies and Applications, IoT 2016, held in GuangZhou, China, in March 2016. The volume contains 26 papers carefully reviewed and selected from 55 submissions focusing on topics such as big data, cloud computing, Internet of Things (IoT). |
| emerging technologies in data analytics: Emerging Technologies Sinan Küfeoğlu, 2022-07-11 This monograph investigates a multitude of emerging technologies including 3D printing, 5G, blockchain, and many more to assess their potential for use to further humanity’s shared goal of sustainable development. Through case studies detailing how these technologies are already being used at companies worldwide, author Sinan Küfeoğlu explores how emerging technologies can be used to enhance progress toward each of the seventeen United Nations Sustainable Development Goals and to guarantee economic growth even in the face of challenges such as climate change. To assemble this book, the author explored the business models of 650 companies in order to demonstrate how innovations can be converted into value to support sustainable development. To ensure practical application, only technologies currently on the market and in use actual companies were investigated. This volume will be of great use to academics, policymakers, innovators at the forefront of green business, and anyone else who is interested in novel and innovative business models and how they could help to achieve the Sustainable Development Goals. This is an open access book. |
| emerging technologies in data analytics: Competitiveness Of Nations 3, The: Emerging Technologies In The Fourth Industrial Revolution Dong-sung Cho, Hwy-chang Moon, 2024-05-17 In the existing reports on national competitiveness and rankings such as IMD World Competitiveness Yearbook and WEF Global Competitiveness Report, there are sizable discrepancies in the ranking order for the same countries. As a result, the reader is often confused because such an outcome creates difficulties for government officials when translating these findings into real-world policies.These discrepancies are actually due to the differences in logic and analytical models used by IMD and WEF. Therefore, in recognizing the problems and limitations of these models, this book presents the IPS model as a new approach. As an extension of Michael Porter's diamond model, it demonstrates a robust set of methodologies as well as offers a number of key policy implications for countries around the world that wish to enhance their national competitiveness.The analytical tools used in this book can be further utilized for other units of analysis such as industries and firms. As this book provides a series of sophisticated methodologies and specific guidelines for enhancing national competitiveness, both academics and practitioners can derive useful implications from this research.Alongside the theoretical frameworks and methodologies for national competitiveness presented in this book, the special theme and focus of this third volume is the fourth industrial revolution and the emerging technologies that are relevant to corporate and national competitiveness.The discussion on the digitalization of business began as early as the 1990s, but emerging technologies such as big data, artificial intelligence, and cloud computing have only been a recent trend. Furthermore, the COVID-19 pandemic has accelerated the adoption of emerging technologies by both firms and countries. Yet, despite the growing importance of emerging technologies, firms and governments seem to be lagging in effectively integrating them into their operations. To address these challenges, this book explains how emerging technologies have affected firms, industries, and countries. It also welcomes discussion on how firms and countries are responding to the changing environment to enhance their competitiveness through these new technologies. |
| emerging technologies in data analytics: Computer Science Engineering and Emerging Technologies Rajeev Sobti, Rachit Garg, Ajeet Kumar Srivastava, Gurpeet Singh Shahi, 2024-06-07 The year 2022 marks the 100th birth anniversary of Kathleen Hylda Valerie Booth, who wrote the first assembly language and designed the assembler and auto code for the first computer systems at Birkbeck College, University of London. She helped design three different machines including the ARC (Automatic Relay Calculator), SEC (Simple Electronic Computer), and APE(X). School of Computer Science and Engineering, under the aegis of Lovely Professional University, pays homage to this great programmer of all times by hosting “BOOTH100”—6th International Conference on Computing Sciences. |
| emerging technologies in data analytics: Human Interaction & Emerging Technologies (IHIET 2023): Artificial Intelligence & Future Applications Tareq Ahram and Redha Taiar, 2023-08-22 Proceedings of the 10th International Conference on Human Interaction and Emerging Technologies, IHIET 2023, August 22-24, 2023, Université Côte d'Azur, Nice, France. |
| emerging technologies in data analytics: Business Models in Emerging Technologies Stylianos Kampakis, Theodosis Mourouzis, Gerard Cardoso, Marialena Zinopoulou, 2022-09-27 This book is a practical guide to two of the most important emerging technologies: data science/AI and blockchain. The world of technology progresses so quickly that we often don’t realize how far we’ve come. Over the last 20 years, technologies like data science, artificial intelligence, the Internet of Things, and blockchain have transformed the world of business, industry, and society. These emerging technologies offer a wide range of opportunities. However, they also create new challenges businesses must face, such as developing new business models, and discovering the best adoption strategies. This book is a practical guide to two of the most important emerging technologies: data science/AI and blockchain. With broad applicability across all sectors, decision-makers would greatly benefit from understanding these fields. |
| emerging technologies in data analytics: Role of Emerging Technologies in Social Science Hitesh Mohapatra, Soumya Ranjan Mishra, Debanjan Pathak, 2024-08-16 In today’s world, technology has seamlessly woven itself into the fabric of our social existence, leaving an indelible mark. This book aims to illuminate the far-reaching impact of technology across various aspects of our lives, including business, commerce, lifestyle, sentiment analysis, and transportation. It delves into both the advantages and drawbacks of technology, emphasizing the need for a delicate balance between our social interactions and its pervasive influence. In today’s interconnected world, technology profoundly influences our social fabric. This book explores its impact across diverse domains—business, commerce, lifestyle, sentiment analysis, and transportation. It delves into both advantages and drawbacks, emphasizing the delicate balance between social interactions and technology, and guides aspiring researchers through cutting-edge topics like blockchain, the Internet of Things, AI, and machine learning. Key takeaways include understanding tech’s role, evaluating pros and cons, and exploring future research. The book caters to universities, graduate colleges, and research centers. |
| emerging technologies in data analytics: Emerging Technologies in Data Mining and Information Security Aboul Ella Hassanien, Siddhartha Bhattacharyya, Satyajit Chakrabati, Abhishek Bhattacharya, Soumi Dutta, 2021-05-04 This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020) held at the University of Engineering & Management, Kolkata, India, during July 2020. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers and case studies related to all the areas of data mining, machine learning, Internet of things (IoT) and information security. |
| emerging technologies in data analytics: IIBF X Taxmann's Emerging Technologies – In-depth Exploration of How Emerging Technologies—such as Data Analytics | Big Data | Blockchain | Machine Learning | AI—are Transforming Banking Indian Institute of Banking & Finance, 2024-10-04 This book comprehensively analyses how technology is revolutionising the banking sector, covering key themes like data analytics, big data, blockchain, machine learning, and artificial intelligence. The book examines how these advancements transform traditional banking operations into digital-first processes, enhance customer experience, streamline operations, and improve risk management. It emphasises the significance of data in decision-making and explores big data tools like Hadoop for managing vast datasets. The book also discusses blockchain's role in fostering transparency and security, while machine learning and AI are analysed for their impact on predictive analysis, personalised services, and fraud detection. It is designed as a self-study guide and uses a modular approach to facilitate independent learning, offering practical examples, case studies, and assessment resources for finance professionals, banking practitioners, and students to adapt to the evolving landscape of digital finance. The Present Publication is the 2024 Edition, authored by Mr Burra Butchi Babu | Former General Manager – Bank of India and vetted by Mr V.A. Prasanth | Former General Manager & Chief Information Officer – Indian Bank. Taxmann exclusively publishes this book for the Indian Institute of Banking and Finance for the certificate course on 'Emerging Technologies' with the following noteworthy features: • [Transforming the Banking Paradigm] The book explains how technology drives the banking sector's transformation, transcending geographical limitations and enhancing operational efficiency. By adopting innovations like digital currencies, big data analytics, machine learning, and blockchain, banks are improving customer experience, increasing transparency, and reducing risks. The book explores these changes in great detail, explaining how technological synergies are paving the way for more innovative, faster, and safer banking operations • [Practical Insights into Technological Adoption] Through real-world applications and expert insights, this book offers a practical perspective on how these emerging technologies are integrated into the banking ecosystem. It discusses how the fusion of finance and technology has fostered new opportunities for growth while addressing the challenges of data security, privacy, and ethical responsibility. Readers are guided to think critically about how these advancements balance the convenience of seamless transactions with the imperative to protect financial identities and safeguard sensitive data • [Comprehensive Coverage through a Modular Approach] To ensure a thorough understanding, the book is structured modularly, covering specific technological areas and their applications in banking. Each module breaks down complex concepts into digestible sections, providing readers with a coherent learning pathway. From the fundamentals of data analytics to the nuanced intricacies of artificial intelligence, the book offers in-depth discussions designed to equip learners with the practical skills necessary for thriving in a technology-driven financial environment • [Self-Learning Resources & Assessment Tools] The book is enriched with self-assessment resources such as multiple-choice questions, terminal questions, and comprehensive summaries, allowing readers to test their knowledge and reinforce their understanding. Every module is carefully structured with learning objectives, chapter overviews, keywords, and references, making it a holistic educational tool. The inclusion of practical examples, case studies, and exercises enhances its relevance for both academic and professional learning environments The book adopts a modular approach, ensuring a coherent and logical flow of content across its four modules, which are as follows: • Module A – Data Analytics o This module is a foundational entry point into data analytics, a key driver of decision-making in modern banking. It introduces emerging technological trends within banks, discussing data extraction, analysis, and visualisation. The module explains the various types of analytics (descriptive, diagnostic, predictive, and prescriptive) and how they extract actionable insights for better financial decision-making. Moreover, the section on immersive technologies such as Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) highlights their role in enhancing customer interactions and operational processes • Module B – Big Data & Hadoop o Big data is a critical component of modern banking and is explored extensively in this module. It discusses how vast datasets are collected, processed, and analysed, enabling banks to make informed decisions, understand customer behaviour, and detect market trends. The module covers topics like Hadoop's ecosystem and architecture, NoSQL databases, and real-life examples showcasing the role of big data in optimising banking processes. It dives into methods for handling large-scale data efficiently and how these insights lead to personalised customer services, risk assessment, and better regulatory compliance • Module C – Blockchain & Digital Currencies o Blockchain is redefining trust and transparency in financial transactions. This module provides an elaborate overview of blockchain, including its types, key features, consensus mechanisms, and transaction flow. The section discusses the rise of digital currencies like Bitcoin and their influence on global finance, highlighting the decentralised nature of blockchain technology and its role in securing financial transactions. It also examines how smart contracts, interoperability, and distributed ledger technology are being implemented in banking to reduce fraud, automate processes, and facilitate seamless cross-border payments • Module D – Machine Learning (ML) in Banking o Machine learning, a cornerstone of artificial intelligence, transforms how banks predict trends, personalise services, and detect fraud. This module introduces the concepts and types of machine learning, covering supervised, unsupervised, and reinforcement learning. Readers are guided through different stages of machine learning, the categorisation of algorithms, and practical examples of how banks use ML for predictive analysis, customer segmentation, credit scoring, and more. It also explores the future trajectory of ML in financial services and its potential to reshape the industry • Module E – Artificial Intelligence (AI) o Artificial Intelligence (AI) has become integral to modernising financial services. This module covers the basics of AI, discussing neural networks, deep learning, natural language processing, and text classification. It examines the architectural framework of neural networks, the role of deep belief networks (DBNs), and generative adversarial networks (GANs) in financial modelling. The book explains the real-world applications of AI, such as chatbots, virtual assistants, fraud detection, automated underwriting, and risk assessment, demonstrating how AI is improving efficiency and customer service in the banking sector. • Emerging Technologies –IoT & Robotic Process Automation (RPA) o Supplementary chapters discuss the Internet of Things (IoT) and Robotic Process Automation (RPA) and their impact on the financial world. By enabling interconnected banking solutions, readers will learn how IoT devices enhance customer experiences. Meanwhile, RPA's role in automating repetitive tasks, reducing manual errors, and increasing operational efficiency is explored, alongside the ethical and practical implications of hyper-automation in banking |
| emerging technologies in data analytics: Data Analytics Applications in Latin America and Emerging Economies Eduardo Rodriguez, 2017-07-28 This book focuses on understanding the analytics knowledge management process and its comprehensive application to various socioeconomic sectors. Using cases from Latin America and other emerging economies, it examines analytics knowledge applications where a solution has been achieved. Written for business students and professionals as well as researchers, the book is filled with practical insight into applying concepts and implementing processes and solutions. The eleven case studies presented in the book incorporate the whole analytics process and are useful reference examples for applying the analytics process for SME organizations in both developing and developed economies. The cases also identify multiple tacit factors to deal with during the implementation of analytics knowledge management processes. These factors, which include data cleaning, data gathering, and interpretation of results, are not always easily identified by analytics practitioners. This book promotes the understanding of analytics methods and techniques. It guides readers through numerous techniques and methods available to analytics practitioners by explaining the strengths and weaknesses of these methods and techniques. |
| emerging technologies in data analytics: Big Data, Emerging Technologies and Intelligence Miah Hammond-Errey, 2024-01-29 This book sets out the big data landscape, comprising data abundance, digital connectivity and ubiquitous technology, and shows how the big data landscape and the emerging technologies it fuels are impacting national security. This book illustrates that big data is transforming intelligence production as well as changing the national security environment broadly, including what is considered a part of national security as well as the relationships agencies have with the public. The book highlights the impact of big data on intelligence production and national security from the perspective of Australian national security leaders and practitioners, and the research is based on empirical data collection, with insights from nearly 50 participants from within Australia’s National Intelligence Community. It argues that big data is transforming intelligence and national security and shows that the impacts of big data on the knowledge, activities and organisation of intelligence agencies is challenging some foundational intelligence principles, including the distinction between foreign and domestic intelligence collection. Furthermore, the book argues that big data has created emerging threats to national security; for example, it enables invasive targeting and surveillance, drives information warfare as well as social and political interference, and challenges the existing models of harm assessment used in national security. The book maps broad areas of change for intelligence agencies in the national security context and what they mean for intelligence communities, and explores how intelligence agencies look out to the rest of society, considering specific impacts relating to privacy, ethics and trust. This book will be of much interest to students of intelligence studies, technology studies, national security and International Relations. |
How the Top 10 Emerging Technologies of 2024 will imp…
Jun 25, 2024 · The World Economic Forum's Top 10 Emerging Technologies of 2024 report lists this year's most …
Top 10 Emerging Technologies of 2024 | World Economic For…
Jun 25, 2024 · These emerging technologiesare disruptive, attractive to investors and researchers, and …
Unlocking clean energy investment in emerging mark…
Apr 21, 2025 · Emerging economies and developing countries house over half the world’s population, but receive …
The Future of Jobs Report 2025 - World Economic Forum
Jan 7, 2025 · Increasing geoeconomic fragmentation, coupled with the rapid adoption of new technologies and …
Discover the must-read cybersecurity stories of the p…
Feb 19, 2025 · This highlights the gap between awareness of AI risks and its unchecked adoption, adding to the …
How the Top 10 Emerging Technologies of 2024 will impact the …
Jun 25, 2024 · The World Economic Forum's Top 10 Emerging Technologies of 2024 report lists this year's most impactful emerging technologies. The list includes ways artificial intelligence is …
Top 10 Emerging Technologies of 2024 | World Economic Forum
Jun 25, 2024 · These emerging technologiesare disruptive, attractive to investors and researchers, and expected to achieve considerable scale within five years. This edition …
Unlocking clean energy investment in emerging markets
Apr 21, 2025 · Emerging economies and developing countries house over half the world’s population, but receive less than 15% of global clean energy investments. Investors often …
The Future of Jobs Report 2025 - World Economic Forum
Jan 7, 2025 · Increasing geoeconomic fragmentation, coupled with the rapid adoption of new technologies and expansion of digital access, has significantly increased cybersecurity …
Discover the must-read cybersecurity stories of the past month
Feb 19, 2025 · This highlights the gap between awareness of AI risks and its unchecked adoption, adding to the growing complexity of cyberspace, where emerging technologies, geopolitical …
The top technology stories from 2024 - The World Economic Forum
Dec 18, 2024 · In June 2024, the Forum released its Top 10 Emerging Technologies of 2024 report. Drawing on insights from scientists, researchers and futurists, the report identifies 10 …
Global Cybersecurity Outlook 2025 | World Economic Forum
Jan 13, 2025 · The Global Cybersecurity Outlook 2025 highlights key trends shaping economies and societies in 2025, along with insights into emerging threats and solutions.
Emerging Technologies | World Economic Forum
6 days ago · Emerging Technologies. 6,217 Stories. Emerging Technologies Entrepreneurship for a New Era. Jun 26, 2025 ...
'Industries in the Intelligent Age': AI, tech & more at Davos 2025
Jan 20, 2025 · These emerging technologiesare disruptive, attractive to investors and researchers, and expected to achieve considerable scale within five years. This edition …
How the top 10 emerging technologies of 2023 will affect us
Jun 26, 2023 · Other emerging technologies range from innovations harnessing the power of AI to reengineering molecular biology. Technology is a relentless disruptor. It changes the context …
