This book enables businesses to understand the difficulties and issues surrounding data collection on an international basis. It explains how to set up, collect and manage name and address data in a business environment from an international perspective. Achieving quality data collection will enable businesses to save money and keep their now sophisticated customers satisfied. The role of the internet and its effect on this area are discussed in detail.

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.

The overall objective of this book is to show that data management is an exciting and valuable capability that is worth time and effort. More specifically it aims to achieve the following goals: 1. To give a “gentle” introduction to the field of DM by explaining and illustrating its core concepts, based on a mix of theory, practical frameworks such as TOGAF, ArchiMate, and DMBOK, as well as results from real-world assignments. 2. To offer guidance on how to build an effective DM capability in an organization.This is illustrated by various use cases, linked to the previously mentioned theoretical exploration as well as the stories of practitioners in the field. The primary target groups are: busy professionals who “are actively involved with managing data”. The book is also aimed at (Bachelor’s/ Master’s) students with an interest in data management. The book is industry-agnostic and should be applicable in different industries such as government, finance, telecommunications etc. Typical roles for which this book is intended: data governance office/ council, data owners, data stewards, people involved with data governance (data governance board), enterprise architects, data architects, process managers, business analysts and IT analysts. The book is divided into three main parts: theory, practice, and closing remarks. Furthermore, the chapters are as short and to the point as possible and also make a clear distinction between the main text and the examples. If the reader is already familiar with the topic of a chapter, he/she can easily skip it and move on to the next.

Medical Data Management is a systematic introduction to the basic methodology of professional clinical data management. It emphasizes generic methods of medical documentation applicable to such diverse tasks as the electronic patient record, maintaining a clinical trials database, and building a tumor registry. This book is for all students in medical informatics and health information management, and it is ideal for both the undergraduate and the graduate levels. The book also guides professionals in the design and use of clinical information systems in various health care settings. It is an invaluable resource for all health care professionals involved in designing, assessing, adapting, or using clinical data management systems in hospitals, outpatient clinics, study centers, health plans, etc. The book combines a consistent theoretical foundation of medical documentation methods outlining their practical applicability in real clinical data management systems. Two new chapters detail hospital information systems and clinical trials. There is a focus on the international classification of diseases (ICD-9 and -10) systems, as well as a discussion on the difference between the two codes. All chapters feature exercises, bullet points, and a summary to provide the reader with essential points to remember. New to the Third Edition is a comprehensive section comprised of a combined Thesaurus and Glossary which aims to clarify the unclear and sometimes inconsistent terminology surrounding the topic.

Libraries organize information and data is information, so it is natural that librarians should help people who need to find, organize, use, or store data. Organizations need evidence for decision making; data provides that evidence. Inventors and creators build upon data collected by others. All around us, people need data. Librarians can help increase the relevance of their library to the research and education mission of their institution by learning more about data and how to manage it. Data Management will guide readers through: Understanding data management basics and best practices. Using the reference interview to help with data management Writing data management plans for grants. Starting and growing a data management service. Finding collaborators inside and outside the library. Collecting and using data in different disciplines.

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.

Written by over 120 data management practitioners, this is the most impressive compilation of data management principals and best practices, ever assembled. It provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure. The equivalent of the PMBOK or the BABOK, the DAMA-DMBOK provides information on: Data Governance; Data Architecture Management; Data Development; Database Operations Management; Data Security Management; Reference & Master Data Management; Data Warehousing & Business Intelligence Management; Document & Content Management; Meta Data Management; Data Quality Management; Professional Development. As an authoritative introduction to data management, the goals of the DAMA-DMBOK Guide are: To build consensus for a generally applicable view of data management functions; To provide standard definitions for commonly used data management functions, deliverables, roles, and other terminology; To document guiding principles for data management; To present a vendor-neutral overview to commonly accepted good practices, widely adopted methods and techniques, and significant alternative approaches; To clarify the scope and boundaries of data management; To act as a reference which guides readers to additional resources for further understanding.