This book presents best selected papers presented at the International Conference on Paradigms of Computing, Communication and Data Sciences (PCCDS 2020), organized by National Institute of Technology, Kurukshetra, India, during 1-3 May 2020. It discusses high-quality and cutting-edge research in the areas of advanced computing, communications and data science techniques. The book is a collection of latest research articles in computation algorithm, communication and data sciences, intertwined with each other for efficiency.

The second of a two volume set on novel methods in harmonic analysis, this book draws on a number of original research and survey papers from well-known specialists detailing the latest innovations and recently discovered links between various fields. Along with many deep theoretical results, these volumes contain numerous applications to problems in signal processing, medical imaging, geodesy, statistics, and data science. The chapters within cover an impressive range of ideas from both traditional and modern harmonic analysis, such as: the Fourier transform, Shannon sampling, frames, wavelets, functions on Euclidean spaces, analysis on function spaces of Riemannian and sub-Riemannian manifolds, Fourier analysis on manifolds and Lie groups, analysis on combinatorial graphs, sheaves, co-sheaves, and persistent homologies on topological spaces. Volume II is organized around the theme of recent applications of harmonic analysis to function spaces, differential equations, and data science, covering topics such as: The classical Fourier transform, the non-linear Fourier transform (FBI transform), cardinal sampling series and translation invariant linear systems. Recent results concerning harmonic analysis on non-Euclidean spaces such as graphs and partially ordered sets. Applications of harmonic analysis to data science and statistics Boundary-value problems for PDE's including the Runge-Walsh theorem for the oblique derivative problem of physical geodesy.

Enterprises and organizations of any kind embedded in today's economic environment are deeply dependent on their ability to take part in collaborations. Consequently, it is strongly required for them to get actively involved for their own benefit in emerging, potentially opportunistic collaborative enterprise networks. The concept of "interoperability" has been defined by INTEROP-VLab as "The ability of an enterprise system or application to interact with others at a low cost in a flexible approach". Consequently, interoperability of organizations appears as a major issue to succeed in building on the fly emerging enterprise networks. The International Conference on Interoperability for Enterprise Systems and Applications (I-ESA 2014) was held under the motto "interoperability for agility, resilience and plasticity of collaborations" on March 26-28, 2014 and organized by the Ecole des Mines d'Albi-Carmaux, France on behalf of the European Laboratory for Enterprise Interoperability (INTEROP-VLab). On March 24-25, co-located with the conference eight workshops and one doctoral symposium were held in four tracks complementing the program of the I-ESA'14 conference. The workshops and the doctoral symposium address areas of greatest current activity focusing on active discussions among the leading researchers in the area of Enterprise Interoperability. This part of the conference helps the community to operate effectively, building co-operative and supportive international links as well as providing new knowledge of on-going research to practitioners. The workshops and doctoral symposium aimed at exploiting new issues, challenges and solutions for Enterprise Interoperability (EI) and associated domains of innovation such as Smart Industry, Internet-Of-Things, Factories of the Future, EI Applications and Standardisation. These proceedings include the short papers from the I-ESA'14 workshops and the doctoral symposium. The book is split up into 9 sections, one for each workshop and one for the doctoral symposium. All sections were organized following four tracks: (1) EI and Future Internet / Factory of the Future; (2) EI Application Domains and IT; (3) EI Standards; (4) EI Doctoral Symposium. For each section, a workshop report is provided summarizing the content and the issues discussed during the sessions. The goal of the first track was to offer a discussion opportunity on interoperability issues regarding the use of Internet of Things on manufacturing environment (Workshops 1 and 3) on one hand, and regarding the potential of innovation derived from the use of digital methods, architectures and services such as Smart Networks (Workshops 2 and 4) on the other hand. The second track focused on particular application domains that are looking for innovative solutions to support their strong collaborative needs. Thus, the track developed one workshop on the use of EI solution for Future City-Logistics (Workshop 5) and one on the use of EI solutions for Crisis / Disaster Management (Workshop 6). The third track studied the recent developments in EI standardization. Two workshops were dedicated to this issue. The first one has proposed to focus on the management of standardization (Workshop 8) and the second one has chosen to work on the new knowledge on standardization developments in the manufacturing service domain (Workshop 9). The last track, the doctoral symposium presented research results from selected dissertations. The session discussed EI knowledge issues, notably in terms of gathering through social networks or Internet of Things and of exploitation through innovative decision support systems.

The book discusses the activities involved in developing an Enterprise Continuity Program (ECP) that will cover both Business Continuity Management (BCM) as well as Disaster Recovery Management (DRM). The creation of quantitative metrics for BCM are discussed as well as several models and methods that correspond to the goals and objectives of the International Standards Organisation (ISO) Technical Committee ISO/TC 292 ""Security and resilience". Significantly, the book contains the results of not only qualitative, but also quantitative, measures of Cyber Resilience which for the first time regulates organizations' activities on protecting their critical information infrastructure. The book discusses the recommendations of the ISO 22301: 2019 standard "Security and resilience - Business continuity management systems - Requirements" for improving the BCM of organizations based on the well-known "Plan-Do-Check-Act" (PDCA) model. It also discusses the recommendations of the following ISO management systems standards that are widely used to support BCM. The ISO 9001 standard ""Quality Management Systems""; ISO 14001 ""Environmental Management Systems""; ISO 31000 ""Risk Management"", ISO/IEC 20000-1 ""Information Technology - Service Management"", ISO/IEC 27001 ""Information Management security systems", ISO 28000 "Specification for security management systems for the supply chain", ASIS ORM.1-2017, NIST SP800-34, NFPA 1600: 2019, COBIT 2019, RESILIA, ITIL V4 and MOF 4.0, etc. The book expands on the best practices of the British Business Continuity Institute's Good Practice Guidelines (2018 Edition), along with guidance from the Disaster Recovery Institute's Professional Practices for Business Continuity Management (2017 Edition). Possible methods of conducting ECP projects in the field of BCM are considered in detail. Based on the practical experience of the author there are examples of Risk Assessment (RA) and Business Impact Analysis (BIA), examples of Business Continuity Plans (BCP) & Disaster Recovery Plans (DRP) and relevant BCP & DRP testing plans. This book will be useful to Chief Information Security Officers, internal and external Certified Information Systems Auditors, senior managers within companies who are responsible for ensuring business continuity and cyber stability, as well as teachers and students of MBA's, CIO and CSO programs.

"This book bridges the fields of health care and data to clarify how to use data to manage pandemics. Written while COVID-19 was raging, it identifies both effective practices and misfires, and is grounded in clear, research-based explanations of pandemics and data strategy....The author has written an essential book for students and professionals in both health care and data. While serving the needs of academics and experts, the book is accessible for the general reader." - Eileen Forrester, CEO of Forrester Leadership Group, Author of CMMI for Services, Guidelines for Superior Service "...Rupa Mahanti explores the connections between data and the human response to the spread of disease in her new book,... She recognizes the value of data and the kind of insight it can bring, while at the same time recognizing that using data to solve problems requires not just technology, but also leadership and courage. This is a book for people who want to better understand the role of data and people in solving human problems." -- Laura Sebastian-Coleman, Author of Meeting the Challenges of Data Quality Management In contrast to the 1918 Spanish flu pandemic which occurred in a non-digital age, the timing of the COVID-19 pandemic intersects with the digital age, characterized by the collection of large amounts of data and sophisticated technologies. Data and technology are being used to combat this digital age pandemic in ways that were not possible in the pre-digital age. Given the adverse impacts of pandemics in general and the COVID-19 pandemic in particular, it is imperative that people understand the meaning, origin of pandemics, related terms, trajectory of a new disease, butterfly effect of contagious diseases, factors governing the pandemic potential of a disease, strategies to combat a pandemic, role of data, data sharing, data strategy, data governance, analytics, and data visualization in managing pandemics, pandemic myths, critical success factors in managing pandemics, and lessons learned. How Data Can Manage Global Health Pandemics: Analyzing and Understanding COVID-19 discusses these elements with special reference to COVID-19. Dr. Rupa Mahanti is a business and data consultant and has expertise in different data management disciplines, business process improvement, regulatory reporting, quality management, and more. She is the author of Data Quality (ASQ Quality Press) and the series Data Governance: The Way Forward (Springer).

You may know SQL basics, but are you taking advantage of its expressive power? This second edition applies a highly practical approach to Structured Query Language (SQL) so you can create and manipulate large stores of data. Based on real-world examples, this updated cookbook provides a framework to help you construct solutions and executable examples in several flavors of SQL, including Oracle, DB2, SQL Server, MySQL, and PostgreSQL. SQL programmers, analysts, data scientists, database administrators, and even relatively casual SQL users will find SQL Cookbook to be a valuable problem-solving guide for everyday issues. No other resource offers recipes in this unique format to help you tackle nagging day-to-day conundrums with SQL. The second edition includes: Fully revised recipes that recognize the greater adoption of window functions in SQL implementations Additional recipes that reflect the widespread adoption of common table expressions (CTEs) for more readable, easier-to-implement solutions New recipes to make SQL more useful for people who aren't database experts, including data scientists Expanded solutions for working with numbers and strings Up-to-date SQL recipes throughout the book to guide you through the basics

Blockchain is a transformative driver for change in all industries. Learn from the latest research and case studies how this technology can and will be used to revolutionize supply chain management. Blockchain and the Supply Chain provides a complete overview of blockchain and the key benefits of integrating this technology into the supply chain. This textbook explains how track and trace can be improved, transaction efficiency increased, visibility enhanced, and more through blockchain. With extensive case studies, learning is underpinned by practical insights as well as cutting-edge research. Clear and accessible information is provided to students on how blockchain will affect supply chain processes, metrics and performance and how to capitalize on the potential of this technology. The fully revised new edition includes the latest information on Enterprise Blockchain, Ethereum and Hyperledger. Focus is also placed on the application of Cloud, Internet of Things (IoT), Machine learning (ML) and other technologies that support supply chains and their integration with blockchain. This textbook highlights how to use blockchain as an enabler and key driver for solutions in the end-to-end supply chain. Online resources include lecture slides and example assignments and quizzes.

Cyber-Physical Systems: A Comprehensive Guide explores the complete sys-tem perspective, underlying theories, modelling, and the applications of Cyber Physical Systems (CPS). It aims to cover all topics ranging from discussion of ru-diments of the system, efficient management, to recent research challenges and issues. Editors aim to present the book in a self-sufficient manner and to achieve this, the book has been edited to include all the aspects of CPS. The book fo-cuses on the concept map of CPS including latest technological interventions; issues, challenges, and the integration of CPS with IoT & Big Data Analytics. This aims to bring together unique contributions on cyber-physical systems research and education with applications in industrial, agriculture, and medical domains. The main aim of the book is to provide a roadmap to the latest advancements to provide optimal solutions in the field of CPS. Features * Coverage of rudiments of the subject * Discussion of recent advancements in the associated field * Considers an audience of diverse domains * Suitable for students (both UG and PG level) and researchers in the field of CPS This book aims to present the emergence of Cyber Physical Systems in response to revolutionary advancements in IoT. While discussing the associated challenges, it also endeavors to devise efficient models which are competent to address these challenges. This book aims to cater to researchers and academicians working in the related field of CPS.

The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex? Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.

Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor's manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.

utilizes the Consolidated Serial Homicide Offender Database, one of the largest and most robust open access databases of multiple murders available illustrated with in-depth case studies of SHOs, such as Felix Vail, Michael Sumpter, the Seminole Heights Killer, and the Austin Bomber provides commentary from those who have used these patterning methods in practice, in addition to laying out how to put the current suite of data tools to use within organizations

Explains concepts of Internet of Everything problems, research challenge goals, and vision in smart cities Based on the most recent innovations, and covering the major challenges in smart cities, between IoT and Big Data Examines security issues and challenges related to data-intensive advances in IoT Addresses the total information science challenges in Internet of Everything enabled technologies Covers the exploring and creating IoT environment related self-adaptive systems

Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area-including healthcare, finance, manufacturing, and marketing-could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy. This is the first such book that provides a comprehensive overview of integrating both cyber security and data science and discusses both theory and practice in secure data science. After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media. This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science.

This book presents state-of-the-art research on security and privacy- preserving for IoT and 5G networks and applications. The accepted book chapters covered many themes, including traceability and tamper detection in IoT enabled waste management networks, secure Healthcare IoT Systems, data transfer accomplished by trustworthy nodes in cognitive radio, DDoS Attack Detection in Vehicular Ad-hoc Network (VANET) for 5G Networks, Mobile Edge-Cloud Computing, biometric authentication systems for IoT applications, and many other applications It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this particular area or those interested in grasping its diverse facets and exploring the latest advances on security and privacy- preserving for IoT and 5G networks.

This book is for anyone who wants to gain an understanding of Blockchain technology and its potential. The book is research-oriented and covers different verticals of Blockchain technology. It discusses the characteristics and features of Blockchain, includes techniques, challenges, and future trends, along with case studies for deeper understanding. Blockchain Technology: Exploring Opportunities, Challenges, and Applications covers the core concepts related to Blockchain technology starting from scratch. The algorithms, concepts, and application areas are discussed according to current market trends and industry needs. It presents different application areas of industry and academia and discusses the characteristics and features of this technology. It also explores the challenges and future trends and provides an understanding of new opportunities. This book is for anyone at the beginner to intermediate level that wants to learn about the core concepts related to Blockchain technology.

Language ability is a unique human trait, and it is indispensable throughout the human life cycle. Blockchain on the other hand, is an innovation that will transform production relationships, change collaboration models and distribution of benefits between people. Language and blockchain seem to have no intersection, yet they are bewilderingly similar in certain ways.When Language Meets Blockchain leads us into an exploratory journey to discover the possibilities of integrating blockchain technology with the language services industry. The author discusses how blockchain technology enables translators to realise their full potential and describes how the role of language can be elevated from a general tool to a driving force through a new concept called Cross-Linguistic Capability. This is a concept that will have very intriguing and beneficial implications for global economic activities.It is demonstrated that language is more than just a tool, it is also a resource and a form of capability. This presents opportunities for cross-linguistic and cross-cultural communications in the era of blockchain, to enable the convergence of linguistic capability with blockchain technology and artificial intelligence. The book's perspective on how the language services industry could adapt to times to embrace blockchain technology for industrial transformation, is both forwarding-looking and value enhancing.

This book aims to provide theoretical and empirical frameworks and highlights the challenges and solutions with using Big Data for Corporate Social Responsibility (CSR) and Sustainability in the field of digital transformation and tourism. Sustainability, Big Data, and Corporate Social Responsibility: Evidence from the Tourism Industry offers a theoretical and empirical framework in the field of digital transformation and applies it to the tourism sector. It discusses Big Data used with CSR and sustainability for the improvement of innovation and highlights the challenges and prospects. It presents a modern insight and approach for use by decision-makers as an application to solve various problems and explores how data collection can shed light on consumer behavior making it possible to account for existing situations and plan for the future. This book is intended to provide a modern insight for researcher, students, professionals, and decision-makers on the application of Big Data to improve CSR and sustainability in the tourism sector.

"In what is certain to be a seminal work on metadata, John Horodyski masterfully affirms the value of metadata while providing practical examples of its role in our personal and professional lives. He does more than tell us that metadata matters-he vividly illustrates why it matters." -Patricia C. Franks, PhD, CA, CRM, IGP, CIGO, FAI, President, NAGARA, Professor Emerita, San Jose State University, USA If data is the language upon which our modern society will be built, then metadata will be its grammar, the construction of its meaning, the building for its content, and the ability to understand what data can be for us all. We are just starting to bring change into the management of the data that connects our experiences. Metadata Matters explains how metadata is the foundation of digital strategy. If digital assets are to be discovered, they want to be found. The path to good metadata design begins with the realization that digital assets need to be identified, organized, and made available for discovery. This book explains how metadata will help ensure that an organization is building the right system for the right users at the right time. Metadata matters and is the best chance for a return on investment on digital assets and is also a line of defense against lost opportunities. It matters to the digital experience of users. It helps organizations ensure that users can identify, discover, and experience their brands in the ways organizations intend. It is a necessary defense, which this book shows how to build.

In this book, Edosa explores common challenges which limit the value that organisations can get from data. What makes his book unique is that he also tackles one of the unspoken barriers to data adoption-fear. Fear of the unknown, fear of the intangible, fear of the investment needed and, yes, fear of losing your job to a machine. With his talent for distilling clarity from complexity, Edosa tackles this and many other challenges. -Tim Carmichael, Chief Data Officer, Chalhoub Group This book offers fresh insight about how to solve the interactional frictions that hamper the flow of data, information and knowledge across organisations. Yet, rather than being stuck with endless polarising debates such as breaking down silos, it shifts focus back towards the ultimate "to what end." -Jacky Wright, Chief Digital Officer (CDO), Microsoft US If you care about AI transformation, empowering people or advancing organisational success in an increasingly digital world, then you should read this book. -Yomi Ibosiola, Chief Data and Analytics Officer, Union Bank A retail giant already struggling due to the Covid-19 pandemic was faced with a disastrous situation when-at the end of a critical investment in an artificial intelligence project that had been meant to save money-it suddenly discovered that its implementation was likely to leave it worse off. An entire critical service stream within an insurer's production system crashed. This critical failure resulted in the detentions of fully insured motorists for allegedly not carrying required insurance. Making Data Work details these two scenarios as well as others illustrating the consequences that arise when organizations do not know how to make data work properly. It is a journey to determine what to do to "make data work" for ourselves and for our organisations. It is a journey to discover how to bring it all together so organisations can enable digital transformation, empower people, and advance organisational success. It is the journey to a world where data and technology finally live up to the hype and deliver better human outcomes, where artificial intelligence can move us from reacting to situations to predicting future occurrences and enabling desirable possibilities.

In this book, Edosa explores common challenges which limit the value that organisations can get from data. What makes his book unique is that he also tackles one of the unspoken barriers to data adoption-fear. Fear of the unknown, fear of the intangible, fear of the investment needed and, yes, fear of losing your job to a machine. With his talent for distilling clarity from complexity, Edosa tackles this and many other challenges. -Tim Carmichael, Chief Data Officer, Chalhoub Group This book offers fresh insight about how to solve the interactional frictions that hamper the flow of data, information and knowledge across organisations. Yet, rather than being stuck with endless polarising debates such as breaking down silos, it shifts focus back towards the ultimate "to what end." -Jacky Wright, Chief Digital Officer (CDO), Microsoft US If you care about AI transformation, empowering people or advancing organisational success in an increasingly digital world, then you should read this book. -Yomi Ibosiola, Chief Data and Analytics Officer, Union Bank A retail giant already struggling due to the Covid-19 pandemic was faced with a disastrous situation when-at the end of a critical investment in an artificial intelligence project that had been meant to save money-it suddenly discovered that its implementation was likely to leave it worse off. An entire critical service stream within an insurer's production system crashed. This critical failure resulted in the detentions of fully insured motorists for allegedly not carrying required insurance. Making Data Work details these two scenarios as well as others illustrating the consequences that arise when organizations do not know how to make data work properly. It is a journey to determine what to do to "make data work" for ourselves and for our organisations. It is a journey to discover how to bring it all together so organisations can enable digital transformation, empower people, and advance organisational success. It is the journey to a world where data and technology finally live up to the hype and deliver better human outcomes, where artificial intelligence can move us from reacting to situations to predicting future occurrences and enabling desirable possibilities.

Tremendous growth in healthcare treatment techniques and methods has led to the emergence of numerous storage and communication problems and need for security among vendors and patients. This book brings together latest applications and state-of-the-art developments in healthcare sector using Blockchain technology. It explains how blockchain can enhance security, privacy, interoperability, and data accessibility including AI with blockchains, blockchains for medical imaging to supply chain management, and centralized management/clearing houses alongside DLT. Features: Includes theoretical concepts, empirical studies and detailed overview of various aspects related to development of healthcare applications from a reliable, trusted, and secure data transmission perspective. Provide insights on business applications of Blockchain, particularly in the healthcare sector. Explores how Blockchain can solve the transparency issues in the clinical research. Discusses AI with Blockchains, ranging from medical imaging to supply chain management. Reviews benchmark testing of AI with Blockchains and its impacts upon medical uses. This book aims at researchers and graduate students in healthcare information systems, computer and electrical engineering.

The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex? Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.

This is the second volume of proceedings including selected papers from the International Conference on IT Convergence and Security (ICITCS) 2017, presenting a snapshot of the latest issues encountered in the field. It explores how IT convergence and security issues are core to most current research, industrial and commercial activities and consists of contributions covering topics including machine learning & deep learning, communication and signal processing, computer vision and applications, future network technology, artificial intelligence and robotics. ICITCS 2017 is the latest in a series of highly successful Inter national Conferences on IT Convergence and Security, previously held in Prague, Czech Republic (2016), Kuala Lumpur, Malaysia (2015), Beijing, China (2014), Macau, China (2013), Pyeong Chang, Korea (2012), and Suwon, Korea (2011).

"Big Data Analytics" will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise.
Guides the reader in assessing the opportunities and value propositionOverview of big data hardware and software architecturesPresents a variety of technologies and how they fit into the big data ecosystem