This book features the refereed proceedings from the 24th British National Conference on Databases, held in Glasgow, Scotland in July 2007. The eighteen full papers and seven poster papers are presented, together with two invited contributions. Papers are organized into topical sections covering data applications, searching XML documents, querying XML documents, XML transformation, clustering and security, data mining, and extraction.

Because of the increased access to high-speed Internet and smart phones, many patients have started to use mobile applications to manage various health needs. These devices and mobile apps are now increasingly used and integrated with telemedicine and telehealth via the medical Internet of Things (IoT). Big Data Management and the Internet of Things for Improved Health Systems is a critical scholarly resource that examines the digital transformation of healthcare. Featuring coverage on a broad range of topics, such as brain computer interface, data reduction techniques, and risk factors, this book is geared towards academicians, practitioners, researchers, and students seeking research on health and well-being data.

How to build and maintain strong data organizations—the Dummies way Data Governance For Dummies offers an accessible first step for decision makers into understanding how data governance works and how to apply it to an organization in a way that improves results and doesn't disrupt. Prep your organization to handle the data explosion (if you know, you know) and learn how to manage this valuable asset. Take full control of your organization’s data with all the info and how-tos you need. This book walks you through making accurate data readily available and maintaining it in a secure environment. It serves as your step-by-step guide to extracting every ounce of value from your data. Identify the impact and value of data in your business Design governance programs that fit your organization Discover and adopt tools that measure performance and need Address data needs and build a more data-centric business culture This is the perfect handbook for professionals in the world of data analysis and business intelligence, plus the people who interact with data on a daily basis. And, as always, Dummies explains things in terms anyone can understand, making it easy to learn everything you need to know.

“Big data” has become a commonly used term to describe large-scale and complex data sets which are difficult to manage and analyze using standard data management methodologies. With applications across sectors and fields of study, the implementation and possible uses of big data are limitless. Effective Big Data Management and Opportunities for Implementation explores emerging research on the ever-growing field of big data and facilitates further knowledge development on methods for handling and interpreting large data sets. Providing multi-disciplinary perspectives fueled by international research, this publication is designed for use by data analysts, IT professionals, researchers, and graduate-level students interested in learning about the latest trends and concepts in big data.

Project management is a system originally developed within the construction industry for controlling schedules, costs, and specifications of large multitask projects. In recent years, manufacturers have discovered that project management's time-tested techniques dovetail neatly with the current thinking on quality control and management in a highly competitive global marketplace. The system has been increasingly recognized for its suitability in the manufacturing process and is now applied in virtually every area of production. One of the foremost proponents of this trend is Adedeji Badiru, an internationally recognized authority on project management, whose books have helped thousands of companies adapt the system to their particular needs. This completely revised Second Edition of Badiru's breakthrough publication, Project Management in Manufacturing and High Technology Operations, focuses on the dramatic increase in the use of high-tech machinery in industrial operations, and seamlessly integrates high-tech themes into a general discussion of project management. An introductory chapter on manufacturing analysis investigates how the latest concepts and techniques of project management are applied to manufacturing. The main body of the book offers a wealth of new material, including discussions of learning curve analysis, basic models for forecasting and inventory control, economic analysis of manufacturing, techniques for data analysis, and the application of expert systems. The chapter on computer applications in project management is completely revised and updated to reflect the enormous strides taken in this area in recent years. This book presents an up-to-date, practical approach to project management in manufacturing. Written by a pioneer in the application of project management to the manufacturing industries, this revised and expanded Second Edition of Project Management in Manufacturing and High Technology Operations reflects the increased use of high-tech machinery in industrial operations and the trends of recent years to apply project management methods to every phase of production. Complete with numerous illustrations, as well as exercises to wrap up each chapter, this Second Edition features: An emphasis on practical examples, including many new case studies, and a full chapter on the lessons learned from the space shuttle Challenger disaster Many new project management concepts and techniques that focus on manufacturing but can be applied to any project A new chapter on manufacturing systems analysis that provides the backdrop for the project analysis that takes place throughout the book Expanded discussions of the latest quantitative and managerial approaches, including learning curve analysis, basic models for forecasting and inventory control, economic analysis of manufacturing, techniques for data analysis, and the application of expert systems A strong international perspective, useful for multinational companies and for academic purposes This book equips engineers and managers with the tools to effectively manage all aspects of a project, including quality control, schedules, and expenses. Used as a text in engineering or business courses, it offers absorbing supplemental reading for students at the upper undergraduate and graduate levels. Professor Badiru has been widely praised for his incisive and highly relevant case studies. In this Second Edition, the case-study approach is expanded so that chapters typically include two real-world examples of the project management techniques or issues in question. In the final chapter, Badiru takes a close and painful look at a high-tech disaster, the explosion of the space shuttle Challenger. He offers rare and instructive insight into the devastating failure of a high-tech project—still poignant, despite the passage of time. Communicative throughout, this volume provides a solid, up-to-date reference for engineers and managers in manufacturing, as well as for consultants and administrators in related fields. Professor Badiru's proven reputation for providing interesting lecture material also makes Project Management in Manufacturing and High Technology Operations especially useful as a technology management text in both engineering and business schools. Cover Design/Illustration: David Levy

Data are an organization's sole, non-depletable, non-degrading, durable asset. Engineered right, data's value increases over time because the added dimensions of time, geography, and precision. To achieve data's full organizational value, there must be dedicated individual to leverage data as assets - a Chief Data Officer or CDO who's three job pillars are: - Dedication solely to leveraging data assets, - Unconstrained by an IT project mindset, and - Reports directly to the business Once these three pillars are set into place, organizations can leverage their data assets. Data possesses properties worthy of additional investment. Many existing CDOs are fatally crippled, however, because they lack one or more of these three pillars. Often organizations have some or all pillars already in place but are not operating in a coordinated manner. The overall objective of this book is to present these pillars in an understandable way, why each is necessary (but insufficient), and what do to about it. - Uncovers that almost all organizations need sophisticated, comprehensive data management education and strategies. - Delivery of organization-wide data success requires a highly focused, full time Chief Data Officer. - Engineers organization-wide data advantage which enables success in the marketplace

As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata

This book constitutes the refereed proceedings of the First International Conference on Big Scientific Data Management, BigSDM 2018, held in Beijing, Greece, in November/December 2018. The 24 full papers presented together with 7 short papers were carefully reviewed and selected from 86 submissions. The topics involved application cases in the big scientific data management, paradigms for enhancing scientific discovery through big data, data management challenges posed by big scientific data, machine learning methods to facilitate scientific discovery, science platforms and storage systems for large scale scientific applications, data cleansing and quality assurance of science data, and data policies.

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. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.

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