Principles of Data Management: Facilitating Information Sharing

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9781902505848: Principles of Data Management: Facilitating Information Sharing

This professional reference guide explains not only the importance of data management and how it can be managed, but the issues facing those involved, and how to address them. Distinctively, this book is not based on a particular propriety system or software, but is business focused, providing the knowledge and techniques required to successfully implement a data management function. 'Principles of Data Management: Facilitating Information Sharing' covers practical and effective approaches to managing corporate data which will improve communication between users and information systems developers, and support an integrated and cost effective approach to data and information resource development. This book explains how to plan and implement a data management function and critically, how to understand and improve the relationships between data and database administrators, systems development teams and business users. Ultimately users become able to obtain the information they need, confident that it is based on correct underlying data. 'Principles of Data Management: Facilitating Information Sharing' also discusses the technical issues that affect data management professionals.

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About the Author:

Keith Gordon is an independent consultant and lecturer specializing in data management and business analysis. A professional soldier for 38 years he has held technical, educational and managerial appointments including serving as head of the army's data management team.

Review:

[...] an interesting and thought-provoking book. -- Pete Cliff * Ariadne, Online Magazine * In this book, Keith Gordon has done an excellent job of laying out the full set of dimensions to be addressed for the effective management of an organization's information. [... ] I strongly recommend this book to someone wanting to understand the connection between the management of information and the kinds of technology that must be employed to do so. -- David C. Hay * The Data Administration Newsletter *

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Book Description BCS, The Chartered Institute for IT/Viva Books, 2008. Softcover. Book Condition: New. First edition. Good data management and information sharing is vital to the success of a modern enterprise. This professional reference guide explains not only the importance of data management to modern business but also the issues facing those involved and how to address them. Distinctively, Principles of Data Management is not based on a particular proprietary system or software, but is business focussed, providing the knowledge and techniques required to successfully implement a data management function. Contents: Data and the enterprise: Information is a key business resource; The relationship between information and data; The importance of the quality of data; The common problems with data; An enterprise-wide view of data; Managing data is a business issue; Summary ? Database development: The database architecture of an information system; An overview of the database development process; Conceptual data modelling (from a project-level perspective); Relational data analysis; The roles of a data model; Physical database design; Summary ? What is data management?: The problems encountered without data management; Data management responsibilities; Roles within data management; The benefits of data management; The relationship between data management and enterprise; Architecture; Summary ? Corporate data modelling: Why develop a corporate data model?; More data modelling concepts; The nature of a corporate data model; How to develop a corporate data model; Corporate data model principles; A final thought; Summary ? Data definition and naming conventions: The elements of a data definition; Data naming conventions; Summary ? Metadata: What is metadata?; Metadata for data management; Metadata for content management; Metadata for describing data values; Summary ? Data quality Data: What is data quality?; Issues associated with poor-quality data; The causes of poor-quality data; The dimensions of data quality; Data model quality; Improving data quality; Summary ? Data Accessibility: Data security; Data integrity; Data recovery; Summary ? Database administration: Database administration reproducibilities; Performance monitoring and tuning; summary ? Repository administration: Repositories, data dictionaries, encyclopedias, catalogs and directories; Repository features; The repository as a centralized source of information; Metadata models ? The management of data management: Techniques and skills for data administration; Techniques and skills for database administration; Techniques and skills for repository administration; The positioning of data management within the enterprise; Summary ? Industry trends and their effects on data management: The use of packages; Distributed data and databases; Data warehousing and data mining; Object orientation and databases; Multimedia and databases; Data and web technology; Summary ? Comparison of data modelling notations ? Heretical and Network databases ? Generic Data models ? An example of a data naming convention ? Metadata models ? A data mining example ? HTML and XML ? XML and relational databases ? References ? Further reading ? Index Printed Pages: 258. Bookseller Inventory # 57632

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Book Description BCS, The Chartered Institute for IT/Viva Books, 2008. Softcover. Book Condition: New. First edition. Good data management and information sharing is vital to the success of a modern enterprise. This professional reference guide explains not only the importance of data management to modern business but also the issues facing those involved and how to address them. Distinctively, Principles of Data Management is not based on a particular proprietary system or software, but is business focussed, providing the knowledge and techniques required to successfully implement a data management function. Contents: Data and the enterprise: Information is a key business resource; The relationship between information and data; The importance of the quality of data; The common problems with data; An enterprise-wide view of data; Managing data is a business issue; Summary ⢠Database development: The database architecture of an information system; An overview of the database development process; Conceptual data modelling (from a project-level perspective); Relational data analysis; The roles of a data model; Physical database design; Summary ⢠What is data management?: The problems encountered without data management; Data management responsibilities; Roles within data management; The benefits of data management; The relationship between data management and enterprise; Architecture; Summary ⢠Corporate data modelling: Why develop a corporate data model?; More data modelling concepts; The nature of a corporate data model; How to develop a corporate data model; Corporate data model principles; A final thought; Summary ⢠Data definition and naming conventions: The elements of a data definition; Data naming conventions; Summary ⢠Metadata: What is metadata?; Metadata for data management; Metadata for content management; Metadata for describing data values; Summary ⢠Data quality Data: What is data quality?; Issues associated with poor-quality data; The causes of poor-quality data; The dimensions of data quality; Data model quality; Improving data quality; Summary ⢠Data Accessibility: Data security; Data integrity; Data recovery; Summary ⢠Database administration: Database administration reproducibilities; Performance monitoring and tuning; summary ⢠Repository administration: Repositories, data dictionaries, encyclopedias, catalogs and directories; Repository features; The repository as a centralized source of information; Metadata models ⢠The management of data management: Techniques and skills for data administration; Techniques and skills for database administration; Techniques and skills for repository administration; The positioning of data management within the enterprise; Summary ⢠Industry trends and their effects on data management: The use of packages; Distributed data and databases; Data warehousing and data mining; Object orientation and databases; Multimedia and databases; Data and web technology; Summary ⢠Comparison of data modelling notations ⢠Heretical and Network databases ⢠Generic Data models ⢠An example of a data naming convention ⢠Metadata models ⢠A data mining example ⢠HTML and XML ⢠XML and relational databases ⢠References ⢠Further reading ⢠Index Printed Pages: 258. Bookseller Inventory # 57632

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