Balamurugan Balusamy

Seifedine Kadry

Amir H. Gandomi

Nandhini Abirami R

Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.

Concepts, Technology, and Architecture

Big Data

Mariya Ouaissa

Vandana Sharma

Munish Sabharwal

"Sustainable Digital Technologies: Trends, Impacts, and Assessments discusses the critical factors leading to sustainable initiatives in a global economy. It highlights the impact of digital technology and Industry 4.0 in today's world. The book focuses on the role, responsibility, and effect of the Internet of Things on digital sustainability and practices. It also describes implementation strategies for green cloud computing and presents additional strategies for sustainable practices in a post-pandemic world"--

Trends, Impacts, and Assessments

Sustainable Digital Technologies

J. Joshua Thomas

L. Godlin Atlas

Web-Driven Applications

Data Fabric Architectures

Rishabha Malviya

Rajesh Kumar Dhanaraj

Sonali Sundram

Gheorghita Ghinea

DEEP LEARNING FOR TREATMENTS The book provides the direction for future research in deep learning in terms of its role in targeted treatment, biological systems, site-specific drug delivery, risk assessment in therapy, etc. Deep Learning for Targeted Treatments describes the importance of the deep learning framework for patient care, disease imaging/detection, and health management. Since deep learning can and does play a major role in a patient’s healthcare management by controlling drug delivery to targeted tissues or organs, the main focus of the book is to leverage the various prospects of the DL framework for targeted therapy of various diseases. In terms of its industrial significance, this general-purpose automatic learning procedure is being widely implemented in pharmaceutical healthcare. Audience The book will be immensely interesting and useful to researchers and those working in the areas of clinical research, disease management, pharmaceuticals, R&D formulation, deep learning analytics, remote healthcare management, healthcare analytics, and deep learning in the healthcare industry.

Transformation in Healthcare

Deep Learning for Targeted Treatments

A Prasanth

Lakshmi D

Sherimon P C

Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT. Key Features Exploits the different prospects of cognitive computing techniques for the IoMT and smart healthcare applications Addresses the significance of IoMT and cognitive computing in the evolution of intelligent medical systems for biomedical applications Describes the different computing techniques of cognitive intelligent systems from a practical point of view: solving common life problems Explores the technologies and tools to utilize IoMT for the transformation and growth of healthcare systems Focuses on the economic, social, and environmental impact of IoMT-enabled smart healthcare systems This book is primarily aimed at graduates, researchers and academicians working in the area of development of the application of the of the application of the IoT in smart healthcare. Industry professionals will also find this book helpful.

Cognitive Computing for Internet of Medical Things

Namita Singh Malik

Elizaveta A Gromova

Smita Gupta

Legal Analytics: The Future of Analytics in Law navigates the crisscrossing of intelligent technology and legal field in building up new landscape of transformation. Legal automation navigation is multidimensional wherein it intends to construct streamline communication, approval and management of legal task. Evolving environment of technology has emphasized need for better automations in legal field from time to time. Although legal scholars took long to embrace Information revolution of legal field. •Describes the historical development of law and automation •Analyses the challenges and opportunities in law and automation •Studies the current research and development in the convergence of Law, Artificial Intelligence and Legal Analytics •Explores the recent emerging trends and technologies that are used by various legal System globally for Crime Prediction & Prevention •Examines the applicability of legal analytics in forensic investigation •Investigates the impact of legal analytics tools and techniques in judicial decision making •Analyses deep learning techniques and its scope in accelerating legal analytics in developed and developing countries • Provides the in-depth analysis of implementation, challenges and issues in the society related to legal analytics The book is primarily aimed at graduates, postgraduates in law & technology, computer science and information technology. Legal practitioners and academicians will also find this book helpful.

The Future of Analytics in Law

Legal Analytics

George Ghinea

Pethuru Raj

T Poongodi

Manju Khari

This book comprehensively conveys the theoretical and practical aspects of IoT and big data analytics with the solid contributions from practitioners as well as academicians. This book examines and expounds the unique capabilities of the big data analytics platforms in capturing, cleansing and crunching IoT device/sensor data in order to extricate actionable insights. A number of experimental case studies and real-world scenarios are incorporated in this book in order to instigate our book readers. This book Analyzes current research and development in the domains of IoT and big data analytics Gives an overview of latest trends and transitions happening in the IoT data analytics space Illustrates the various platforms, processes, patterns, and practices for simplifying and streamlining IoT data analytics The Internet of Things and Big Data Analytics: Integrated Platforms and Industry Use Cases examines and accentuates how the multiple challenges at the cusp of IoT and big data can be fully met. The device ecosystem is growing steadily. It is forecast that there will be billions of connected devices in the years to come. When these IoT devices, resource-constrained as well as resource-intensive, interact with one another locally and remotely, the amount of multi-structured data generated, collected, and stored is bound to grow exponentially. Another prominent trend is the integration of IoT devices with cloud-based applications, services, infrastructures, middleware solutions, and databases. This book examines the pioneering technologies and tools emerging and evolving in order to collect, pre-process, store, process and analyze data heaps in order to disentangle actionable insights.

Integrated Platforms and Industry Use Cases

The Internet of Things and Big Data Analytics

Green Computing in Smart Cities: Simulation and Techniques

Balamurugan Balusamy

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