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.

Equip your students with a management-focused overview of information security as well as the tools to effectively administer it with Whitman/Mattord's MANAGEMENT OF INFORMATION SECURITY, Sixth Edition.

More than ever, we need to prepare information security management students to build and staff security programs capable of securing systems and networks to meet the challenges in a world where continuously emerging threats, ever-present attacks and the success of criminals illustrate weaknesses in current information technologies. This text offers an exceptional blend of skills and experiences to administer and manage the more secure computing environments that organizations need.

Reflecting the latest developments from the field, it includes updated coverage of NIST, ISO and security governance along with emerging concerns like Ransomware, Cloud Computing and the Internet of Things.

Safety of Web Applications: Risks, Encryption and Handling Vulnerabilities with PHP explores many areas that can help computer science students and developers integrate security into their applications. The Internet is not secure, but it's very friendly as a tool for storing and manipulating data. Customer confidence in Internet software is based on it's ability to prevent damage and attacks, but secure software is complicated, depending on several factors, including good risk estimation, good code architecture, cyphering, web server configuration, coding to prevent the most common attacks, and identification and rights allocation.

Big Data and Smart Service Systems presents the theories and applications regarding Big Data and smart service systems, data acquisition, smart cities, business decision-making support, and smart service design. The rapid development of computer and Internet technologies has led the world to the era of Big Data. Big Data technologies are widely used, which has brought unprecedented impacts on traditional industries and lifestyle. More and more governments, business sectors, and institutions begin to realize data is becoming the most valuable asset and its analysis is becoming the core competitiveness.

Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics.

The originality of this book, which deals with such a new subject matter, lies in the application of methods and concepts never used before - such as ontologies and taxonomies, as well as thesauri - to the ordering of knowledge based on primary information. Chapters in the book also examine the study of ontologies, taxonomies and thesauri from the perspective of systematics and general systems theory. Ontologies, Taxonomies and Thesauri in Systems Science and Systematics will be extremely useful to those operating within the network of related fields, which includes documentation and information science.
Ontologies and TaxonomyKnowledge classification SystemsThesauri

Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining.
Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions.
Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data miningA valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions

Almost every organization seeks a simple means of managing, publishing and/or providing searchable web access to information. Written by a knowledgeable web developer, this book demonstrates the simplicity, cost-effectiveness, and versatility of designing database driven web applications with Open Source resources. Case studies of real world implementations address both theoretical aspects and practical considerations of developing applications with the easy-to-use PHP scripting language and powerful MySQL relational database. Project organization and design issues are considered along with basic coding examples, accessibility standards and implementation advice.
Introduces popular Open Source database tools (MySQL/PHP) and basic development skills, bringing database driven technology within the reach of any web developerExplores strategies for improving content management, web publishing and information accessUses non-technical language and presents seven university library web database case studies"

The study and application of spatial information systems have been developed primarily from the use of computers in the geosciences. These systems have the principle functions of capturing, storing, representing, manipulating, and displaying data in 2-D and 3-D worlds. This book approaches its subject from the perspectives of informatics and geography, presenting methods of conceptual modeling developed in computer science that provide valuable aids for resolving spatial problems. This book is an essential textbook for both students and practitioners. It is indispensable for academic geographers, computer scientists, and the GIS professional.
Key Features
* Serves as the first comprehensive textbook on the field of Spatial Information Systems (also known as Geographic Information Systems)
* Contains extensive illustrations
* Presents numerous detailed examples

Database Solutions: A step-by-step guide to building databases 2/eAre you responsible for designing and creating the databases that keep your business running? Or are you studying for a module in database design? If so, Database Solutions is for you This fully revised and updated edition will make the database design and build process smoother, quicker and more reliable.Recipe for database success Take one RDMS - any of the major commercial products will do: Oracle, Informix, SQL Server, Access, Paradox Add one thorough reading of Database Solutions if you are an inexperienced database designer, or one recap of the methodology if you are an old hand Use the design and implementation frameworks to plan your timetable, use a common data model that fits your requirements and adapt as necessaryFeatures Includes hints and tips for success with comprehensive guidance on avoiding pitfalls and traps Shows how to create data models using the UML design notation Includes two full-length coded example databases written on Microsoft Access 2002 and Oracle 9i, plus 15 sample data models to adapt to your needs, chosen from seven common business areasNew for this edition New chapters on SQL (St

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

For Database Systems and Database Design and Application courses offered at the junior, senior and graduate levels in Computer Science departments. Written by well-known computer scientists, this introduction to database systems offers a comprehensive approach, focusing on database design, database use, and implementation of database applications and database management systems. The first half of the book provides in-depth coverage of databases from the point of view of the database designer, user, and application programmer. It covers the latest database standards SQL:1999, SQL/PSM, SQL/CLI, JDBC, ODL, and XML, with broader coverage of SQL than most other texts. The second half of the book provides in-depth coverage of databases from the point of view of the DBMS implementor. It focuses on storage structures, query processing, and transaction management. The book covers the main techniques in these areas with broader coverage of query optimisation than most other texts, along with advanced topics including multidimensional and bitmap indexes, distributed transactions, and information integration techniques.

Databases are often viewed as the end product rather than as a tool in the work place. This book has been written to address this need, using straightforward examples and assessing different ways of storing information. It is a practical guide to collecting data and using Microsoft Access to transform it into useful information. Written for both Business Studies students and professionals, it adopts a functional approach which teaches theory by practical example. 'Jargon buster' sidebars explain the terminology related to database theory, while the revision questions at the end of each unit aid comprehension. This straightforward approach means that the text is ideal for self-study.

This thought-provoking book challenges the way we think about the regulation of cryptoassets based on cryptographic consensus technology. Bringing a timely new perspective, Syren Johnstone critiques the application of a financial regulation narrative to cryptoassets, questions the assumptions on which it is based, and considers its impact on industry development. Providing new insights into the dynamics of oversight regulation, Johnstone argues that the financial narrative stifles the 'New Prospect' for the formation of novel commercial relationships and institutional arrangements. The book asks whether regulations developed in the 20th century remain appropriate to apply to a technology emerging in the 21st, suggesting it is time to think about how to regulate for ecosystem development. Johnstone concludes with proposals for reform, positing a new framework that facilitates industry aspirations while remaining sustainable and compatible with regulatory objectives. Rethinking the Regulation of Cryptoassets will be an invaluable read for policy makers, regulators and technologists looking for a deeper understanding of the issues surrounding cryptoasset regulation and possible alternative approaches. It will also be of interest to scholars and students researching the intersection of law, technology, regulation and finance.

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data.

With the growing maturity and stability of digitization and edge technologies, vast numbers of digital entities, connected devices, and microservices interact purposefully to create huge sets of poly-structured digital data. Corporations are continuously seeking fresh ways to use their data to drive business innovations and disruptions to bring in real digital transformation. Data science (DS) is proving to be the one-stop solution for simplifying the process of knowledge discovery and dissemination out of massive amounts of multi-structured data. Supported by query languages, databases, algorithms, platforms, analytics methods and machine and deep learning (ML and DL) algorithms, graphs are now emerging as a new data structure for optimally representing a variety of data and their intimate relationships. Compared to traditional analytics methods, the connectedness of data points in graph analytics facilitates the identification of clusters of related data points based on levels of influence, association, interaction frequency and probability. Graph analytics is being empowered through a host of path-breaking analytics techniques to explore and pinpoint beneficial relationships between different entities such as organizations, people and transactions. This edited book aims to explain the various aspects and importance of graph data science. The authors from both academia and industry cover algorithms, analytics methods, platforms and databases that are intrinsically capable of creating business value by intelligently leveraging connected data. This book will be a valuable reference for ICTs industry and academic researchers, scientists and engineers, and lecturers and advanced students in the fields of data analytics, data science, cloud/fog/edge architecture, internet of things, artificial intelligence/machine and deep learning, and related fields of applications. It will also be of interest to analytics professionals in industry and IT operations teams.