The third edition of Database Principles maintains its engaging writing style and brevity; its unique balance between theory and practice; and its wealth of examples throughout the text. It provides a solid and practical foundation for the design, implementation and management of database systems. The new edition has been updated with all the latest developments and technologies and incorporates a generous number of localised and motivating business vignettes that tie the concepts to real-life situations. The coverage of SQL provides numerous examples and simpler explanations that focus on areas most important for a database career. This edition is suitable for a first course in databases at undergraduate level and will also provide essential material for conversion postgraduate courses. Providing comprehensive and practical coverage of core database concepts, it is an ideal text not only for those studying database management systems in the context of computer science, but also those on courses in the areas of information systems and business information technology.

The Data Management Body of Knowledge (DAMA-DMBOK2) presents a comprehensive view of the challenges, complexities, and value of effective data management.

Today's organizations recognize that managing data is central to their success. They recognize data has value and they want to leverage that value. As our ability and desire to create and exploit data has increased, so too has the need for reliable data management practices.

The second edition of DAMA International's Guide to the Data Management Body of Knowledge (DAMA-DMBOK2) updates and augments the highly successful DMBOK1. An accessible, authoritative reference book written by leading thinkers in the field and extensively reviewed by DAMA members, DMBOK2 brings together materials that comprehensively describe the challenges of data management and how to meet them by:

• Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas.
• Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics.
• Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals.

CompTIA (R) Data+ DA0-001 Exam Cram is an all-inclusive study guide designed to help you pass the CompTIA Data+ DA0-001 exam. Prepare for test day success with complete coverage of exam objectives and topics, plus hundreds of realistic practice questions. Extensive prep tools include quizzes, Exam Alerts, and our essential last-minute review CramSheet. The powerful Pearson Test Prep practice software provides real-time assessment and feedback with two complete exams. Covers the critical information needed to score higher on your Data+ DA0-001 exam! Understand data concepts, environments, mining, analysis, visualization, governance, quality, and controls Work with databases, data warehouses, database schemas, dimensions, data types, structures, and file formats Acquire data and understand how it can be monetized Clean and profile data so it;s more accurate, consistent, and useful Review essential techniques for manipulating and querying data Explore essential tools and techniques of modern data analytics Understand both descriptive and inferential statistical methods Get started with data visualization, reporting, and dashboards Leverage charts, graphs, and reports for data-driven decision-making Learn important data governance concepts

As the world has entered the era of big data, there is a need to give a semantic perspective to the data to find unseen patterns, derive meaningful information, and make intelligent decisions. This 2-volume handbook set is a unique, comprehensive, and complete presentation of the current progress and future potential explorations in the field of data science and related topics. Handbook of Data Science with Semantic Technologies provides a roadmap for a new trend and future development of data science with semantic technologies. The first volume serves as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for both academic researchers and industry professionals. The second volume provides a roadmap for the deployment of semantic technologies in the field of data science that enables users to create intelligence through these technologies by exploring the opportunities while eradicating the current and future challenges. The set explores the optimal use of these technologies to provide the maximum benefit to the user under one comprehensive source. This set consisting of two separate volumes can be utilized independently or together as an invaluable resource for students, scholars, researchers, professionals, and practitioners in the field.

Learn how to create and profit from NFTs The NFT Handbook is a detailed guide on how to create, sell and buy non-fungible tokens without the need for a technical background. Learn exactly what NFTs are, how they evolved, and why they have value. We'll delve into the different types and aspects of NFTs and discuss the different NFT marketplaces and the pros and cons of each. Create Your Own NFTs Step by step instructions on all aspects of NFT creation, including what types of content to use, where to source content, adding artistic design, writing the NFT's description, adding optional unlockable content and setting an optional ongoing royalty. Mint Your NFTs You'll learn the process of how to get your NFTs on the blockchain. Sell Your NFTs We'll go through the whole process including creating a collection, and the different options such as setting a price or starting an auction. Buy NFTs What you'll need to bid on and purchase NFTs, and how to avoid getting scammed. You'll also get a primer on blockchain, particularly the Ethereum cryptocurrency and "gas" fees. You'll also be shown step by step how to create, secure and fund your own cryptocurrency wallet, where you'll store your NFTs and cryptocurrency. Whether you're experienced with the blockchain and crypto or a complete noob (beginner), The NFT Handbook will guide you in the process of creating, minting, selling and buying NFTs.

Database System Concepts by Silberschatz, Korth and Sudarshan is now in its 7th edition and is one of the cornerstone texts of database education. It presents the fundamental concepts of database management in an intuitive manner geared toward allowing students to begin working with databases as quickly as possible. The text is designed for a first course in databases at the junior/senior undergraduate level or the first year graduate level. It also contains additional material that can be used as supplements or as introductory material for an advanced course. Because the authors present concepts as intuitive descriptions, a familiarity with basic data structures, computer organization, and a high-level programming language are the only prerequisites. Important theoretical results are covered, but formal proofs are omitted. In place of proofs, figures and examples are used to suggest why a result is true.

Build a solid foundation in data analysis skills and pursue a coveted Data+ certification with this intuitive study guide CompTIA Data+ Study Guide: Exam DA0-001 delivers easily accessible and actionable instruction for achieving data analysis competencies required for the job and on the CompTIA Data+ certification exam. You'll learn to collect, analyze, and report on various types of commonly used data, transforming raw data into usable information for stakeholders and decision makers. With comprehensive coverage of data concepts and environments, data mining, data analysis, visualization, and data governance, quality, and controls, this Study Guide offers: All the information necessary to succeed on the exam for a widely accepted, entry-level credential that unlocks lucrative new data analytics and data science career opportunities 100% coverage of objectives for the NEW CompTIA Data+ exam Access to the Sybex online learning resources, with review questions, full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms Ideal for anyone seeking a new career in data analysis, to improve their current data science skills, or hoping to achieve the coveted CompTIA Data+ certification credential, CompTIA Data+ Study Guide: Exam DA0-001 provides an invaluable head start to beginning or accelerating a career as an in-demand data analyst.

Gillenson's new edition of "Fundamentals of Database Management Systems" provides concise coverage of the fundamental topics necessary for a deep understanding of the basics. In this issue, there is more emphasis on a practical approach, with new "your turn" boxes and much more coverage in a separate supplement on how to implement databases with Access.

In every chapter, the author covers concepts first, then show how they're implemented in continuing case(s.) "Your Turn" boxes appear several times throughout the chapter to apply concepts to projects. And "Concepts in Action" boxes contain examples of concepts used in practice. This pedagogy is easily demonstrable and the text also includes more hands-on exercises and projects and a standard diagramming style for the data modeling diagrams. Furthermore, revised and updated content and organization includes more coverage on database control issues, earlier coverage of SQL, and new coverage on data quality issues.

Confidently shepherd your organization's implementation of Microsoft Dynamics 365 to a successful conclusion In Mastering Microsoft Dynamics 365 Implementations, accomplished executive, project manager, and author Eric Newell delivers a holistic, step-by-step reference to implementing Microsoft's cloud-based ERP and CRM business applications. You'll find the detailed and concrete instructions you need to take your implementation project all the way to the finish line, on-time, and on-budget. You'll learn: The precise steps to take, in the correct order, to bring your Dynamics 365 implementation to life What to do before you begin the project, including identifying stakeholders and building your business case How to deal with a change management throughout the lifecycle of your project How to manage conference room pilots (CRPs) and what to expect during the sessions Perfect for CIOs, technology VPs, CFOs, Operations leaders, application directors, business analysts, ERP/CRM specialists, and project managers, Mastering Microsoft Dynamics 365 Implementations is an indispensable and practical reference for guiding your real-world Dynamics 365 implementation from planning to completion.

Monetize your company's data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company's data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that's most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework - A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don't worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you're already a data science expert? Then you really won't want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you'll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one's talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you're new to the data science field or already a decade in, you're sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company's data by picking up your copy today.

This OCP Oracle Certified Professional Java SE 11 Programmer I Study Guide: Exam 1Z0-815 and the Programmer II Study Guide: Exam 1Z0-816 were published before Oracle announced major changes to its OCP certification program and the release of the new Developer 1Z0-819 exam. No matter the changes, rest assured both of the Programmer I and II Study Guides cover everything you need to prepare for and take Exam 1Z0-819. If you've purchased one of the Programmer Study Guides, purchase the other one and you'll be all set. NOTE: The OCP Java SE 11 Programmer I Exam 1Z0-815 and Programmer II Exam 1Z0-816 have been retired (as of October 1, 2020), and Oracle has released a new Developer Exam 1Z0-819 to replace the previous exams. The Upgrade Exam 1Z0-817 remains the same. The completely-updated preparation guide for the new OCP Oracle Certified Professional Java SE 11 Programmer II exam--covers Exam 1Z0-816 Java, a platform-independent, object-oriented programming language, is used primarily in mobile and desktop application development. It is a popular language for client-side cloud applications and the principal language used to develop Android applications. Oracle has recently updated its Java Programmer certification tracks for Oracle Certified Professional. OCP Oracle Certified Professional Java SE 11 Programmer II Study Guide ensures that you are fully prepared for this difficult certification exam. Covering 100% of exam objectives, this in-depth study guide provides comprehensive coverage of the functional-programming knowledge necessary to succeed. Every exam topic is thoroughly and completely covered including exceptions and assertions, class design, generics and collections, threads, concurrency, IO and NIO, and more. Access to Sybex's superior online interactive learning environment and test bank--including self-assessment tests, chapter tests, bonus practice exam questions, electronic flashcards, and a searchable glossary of important terms--provides everything you need to be fully prepared on exam day. This must-have guide: Covers all exam objectives such as inheriting abstract classes and interfaces, advanced strings and localization, JDBC, and Object-Oriented design principles and patterns Explains complex material and reinforces your comprehension and retention of important topics Helps you master more advanced areas of functional programming Demonstrates practical methods for building Java solutions OCP Oracle Certified Professional Java SE 11 Programmer II Study Guide will prove invaluable for anyone seeking achievement of this challenging exam, as well as junior- to senior-level programmers who uses Java as their primary programming language.

At only nineteen years old Vitalik Buterin published a visionary paper outlining the ideas behind what would become Ethereum. He proposed to take what Bitcoin did for currency - to end the central control of governments and corporations - and apply it to society as a whole. Now, less than a decade later, Ethereum is the second-most-valuable cryptocurrency and has opened the gates for the extraordinary new world of NFT artworks, virtual real estate in the metaverse and decentralised autonomous organisations. The essays in Proof of Stake reveal Buterin as a lively, creative thinker, relentlessly curious and adventurous in exploring the fascinating social, economic and political possibilities of his invention, and will guide future generations of Ethereum's community of radicals and builders.

Pulling aside the curtain of 'Big Data' buzz, this book introduces C-suite and other non-technical senior leaders to the essentials of obtaining and maintaining accurate, reliable data, especially for decision-making purposes. Bad data begets bad decisions, and an understanding of data fundamentals - how data is generated, organized, stored, evaluated, and maintained - has never been more important when solving problems such as the pandemic-related supply chain crisis. This book addresses the data-related challenges that businesses face, answering questions such as: What are the characteristics of high-quality data? How do you get from bad data to good data? What procedures and practices ensure high-quality data? How do you know whether your data supports the decisions you need to make? This clear and valuable resource will appeal to C-suite executives and top-line managers across industries, as well as business analysts at all career stages and data analytics students.

This book provides readers to the vision of Society 5.0, which was originally proposed in the fifth Basic Science and Technology Plan by Japan's government for a technology-based, human-centered society, emerging from the 4th industrial revolution (Industry 4.0). The implementation of AI and other modern techniques in a smart society requires automated data scheduling and analysis using smart applications, a smart infrastructure, smart systems, and a smart network. Features Provides an overview of basic concepts of Society 5.0 as well as the main pillars that supports the implementation of Society 5.0. Contains the most recent research analysis in the domain of computer vision, signal processing and computing sciences for facilitating the smart homes, buildings, transport, facilities, environmental conditions and cities, and the benefits these offer to a nation. Presents the readers with practical approaches of using AI and other algorithms for smart ecosystem to deals with human dynamics, the social objects, and their relations. Deals with the utilization of AI tools and other modern techniques for smart society as well as the current challenging issues and its solutions for transformation to Society 5.0. This book is aimed at graduate and post graduate students, researchers, academicians working in the field of computer science, artificial intelligence, and machine learning.

The crypto era has arrived, and business will never be the same. Real applications of crypto technology are growing exponentially: cryptocurrency payments are moving frictionlessly across borders; NFTs are generating real value for creators and consumers alike; and new blockchain-enabled business models are being built around decentralized finance and Web3. What do you and your company need to know and do today to create new opportunities and avoid disruption? Crypto: The Insights You Need from Harvard Business Review will show you how innovative organizations of all kinds are embracing decentralized technology, reinventing themselves, and thriving in the new age of crypto. Business is changing. Will you adapt or be left behind? Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. Featuring HBR's smartest thinking on fast-moving issues-blockchain, cybersecurity, AI, and more-each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas-and prepare you and your company for the future.

The book equips students with the end-to-end skills needed to do data science. That means gathering, cleaning, preparing, and sharing data, then using statistical models to analyse data, writing about the results of those models, drawing conclusions from them, and finally, using the cloud to put a model into production, all done in a reproducible way. At the moment, there are a lot of books that teach data science, but most of them assume that you already have the data. This book fills that gap by detailing how to go about gathering datasets, cleaning and preparing them, before analysing them. There are also a lot of books that teach statistical modelling, but few of them teach how to communicate the results of the models and how they help us learn about the world. Very few data science textbooks cover ethics, and most of those that do, have a token ethics chapter. Finally, reproducibility is not often emphasised in data science books. This book is based around a straight-forward workflow conducted in an ethical and reproducible way: gather data, prepare data, analyse data, and communicate those findings. This book will achieve the goals by working through extensive case studies in terms of gathering and preparing data, and integrating ethics throughout. It is specifically designed around teaching how to write about the data and models, so aspects such as writing are explicitly covered. And finally, the use of GitHub and the open-source statistical language R are built in throughout the book. Key Features: Extensive code examples. Ethics integrated throughout. Reproducibility integrated throughout. Focus on data gathering, messy data, and cleaning data. Extensive formative assessment throughout.

This new volume explores a plethora of blockchain-based solutions for big data and IoT applications, looking at advances in real-world applications in several sectors, including higher education, cybersecurity, agriculture, business and management, healthcare and biomedical science, construction and project management, smart city development, and others. Chapters explore emerging technology to combat the ever-increasing threat of security to computer systems and offer new architectural solutions for problems encountered in data management and security. The chapters help to provide a high level of understanding of various blockchain algorithms along with the necessary tools and techniques. The novel architectural solutions in the deployment of blockchain presented here are the core of the book.

While most discoverability evaluation studies in the Library and Information Science field discuss the intersection of discovery layers and library systems, this book looks specifically at digital repositories, examining discoverability from the lenses of system structure, user searches, and external discovery avenues. Discoverability, the ease with which information can be found by a user, is the cornerstone of all successful digital information platforms. Yet, most digital repository practitioners and researchers lack a holistic and comprehensive understanding of how and where discoverability happens. This book brings together current understandings of user needs and behaviors and poses them alongside a deeper examination of digital repositories around the theme of discoverability. It examines discoverability in digital repositories from both user and system perspectives by exploring how users access content (including their search patterns and habits, need for digital content, effects of outreach, or integration with Wikipedia and other web-based tools) and how systems support or prevent discoverability through the structure or quality of metadata, system interfaces, exposure to search engines or lack thereof, and integration with library discovery tools. Discoverability in Digital Repositories will be particularly useful to digital repository managers, practitioners, and researchers, metadata librarians, systems librarians, and user studies, usability and user experience librarians. Additionally, and perhaps most prominently, this book is composed with the emerging practitioner in mind. Instructors and students in Library and Information Science and Information Management programs will benefit from this book that specifically addresses discoverability in digital repository systems and services.

Blockchain technologies, as an emerging distributed architecture and computing paradigm, have accelerated the development/application of the Cloud/GPU/Edge Computing, Artificial Intelligence, cyber physical systems, social networking, crowdsourcing and crowdsensing, 5G, trust management, and finance. The popularity and rapid development of Blockchain brings many technical and regulatory challenges for research and academic communities. This book will feature contributions from experts on topics related to performance, benchmarking, durability, robustness, as well data gathering and management, algorithms, analytics techniques for transactions processing, and implementation of applications.

Designed to offer an accessible set of case studies and analyses of ethical dilemmas in data science. This book will be suitable for technical readers in data science who want to understand diverse ethical approaches to AI.

'Natural Language Processing in the Real World' is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real-world where there may not be an existing rich dataset. This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented. This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects. .

Digital Image Processing with C++ presents the theory of digital image processing, and implementations of algorithms using a dedicated library. Processing a digital image means transforming its content (denoising, stylizing, etc.), or extracting information to solve a given problem (object recognition, measurement, motion estimation, etc.). This book presents the mathematical theories underlying digital image processing, as well as their practical implementation through examples of algorithms implemented in the C++ language, using the free and easy-to-use CImg library. Chapters cover in a broad way the field of digital image processing and proposes practical and functional implementations of each method theoretically described. The main topics covered include filtering in spatial and frequency domains, mathematical morphology, feature extraction and applications to segmentation, motion estimation, multispectral image processing and 3D visualization. Students or developers wishing to discover or specialize in this discipline, teachers and researchers wishing to quickly prototype new algorithms, or develop courses, will all find in this book material to discover image processing or deepen their knowledge in this field.

The internet has launched the world into an era into which enormous amounts of data are generated every day through technologies with both positive and negative consequences. This often refers to big data . This book explores big data in organisations operating in the criminology and criminal justice fields. Big data entails a major disruption in the ways we think about and do things, which certainly applies to most organisations including those operating in the criminology and criminal justice fields. Big data is currently disrupting processes in most organisations - how different organisations collaborate with one another, how organisations develop products or services, how organisations can identify, recruit, and evaluate talent, how organisations can make better decisions based on empirical evidence rather than intuition, and how organisations can quickly implement any transformation plan, to name a few. All these processes are important to tap into, but two underlying processes are critical to establish a foundation that will permit organisations to flourish and thrive in the era of big data - creating a culture more receptive to big data and implementing a systematic data analytics-driven process within the organisation. Written in a clear and direct style, this book will appeal to students and scholars in criminology, criminal justice, sociology, and cultural studies but also to government agencies, corporate and non-corporate organisations, or virtually any other institution impacted by big data.

Since databases are the primary repositories of information for today's organizations and governments, database security has become critically important. Introducing the concept of multilevel security in relational databases, this book provides a comparative study of the various models that support multilevel security policies in the relational database-illustrating the strengths and weaknesses of each model. Multilevel Security for Relational Databases covers multilevel database security concepts along with many other multilevel database security models and techniques. It presents a prototype that readers can implement as a tool for conducting performance evaluations to compare multilevel secure database models. The book supplies a complete view of an encryption-based multilevel security database model that integrates multilevel security for the relational database with a system that encrypts each record with an encryption key according to its security class level. This model will help you utilize an encryption system as a second security layer over the multilevel security layer for the database, reduce the multilevel database size, and improve the response time of data retrieval from the multilevel database. Considering instance-based multilevel database security, the book covers relational database access controls and examines concurrency control in multilevel database security systems. It includes database encryption algorithms, simulation programs, and Visual studio and Microsoft SQL Server code.