Dictionary of Data Processing
Author | : Jeff Maynard |
Publisher | : Butterworth-Heinemann |
Total Pages | : 296 |
Release | : 1981 |
Genre | : Computers |
ISBN | : |
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Author | : Jeff Maynard |
Publisher | : Butterworth-Heinemann |
Total Pages | : 296 |
Release | : 1981 |
Genre | : Computers |
ISBN | : |
Author | : Jerry M. Rosenberg |
Publisher | : |
Total Pages | : 760 |
Release | : 1987-09-09 |
Genre | : Business & Economics |
ISBN | : |
The only dictionary that links all three information technologies, this definitive reference source shows the relationship between them and makes their often confusing and intimidating vocabularies understandable to experts and laypersons alike. This edition has been extensively updated and expanded to reflect the tremendous advances in these areas since its publication in 1984. Its alphabetical format gives easy access to more than 10,000 listings, including new entries covering AI, integration, supercomputers, telecommunication, and much more.
Author | : Alfred Wittmann |
Publisher | : Elsevier Publishing Company |
Total Pages | : 357 |
Release | : 1987-01 |
Genre | : Reference |
ISBN | : 9780444989475 |
Author | : Ronald Gordon Anderson |
Publisher | : Financial Times/Prentice Hall |
Total Pages | : 164 |
Release | : 1984 |
Genre | : Computers |
ISBN | : |
Author | : LILIAN TROLLHANN, ALFRED WITTMANN |
Publisher | : |
Total Pages | : 314 |
Release | : 1964 |
Genre | : |
ISBN | : |
Author | : K. Hofstad |
Publisher | : |
Total Pages | : 455 |
Release | : 1997-01-01 |
Genre | : |
ISBN | : 9780320023958 |
Author | : Dama International |
Publisher | : |
Total Pages | : 0 |
Release | : 2011 |
Genre | : Business & Economics |
ISBN | : 9781935504122 |
A glossary of over 2,000 terms which provides a common data management vocabulary for IT and Business professionals, and is a companion to the DAMA Data Management Body of Knowledge (DAMA-DMBOK). Topics include: Analytics & Data Mining Architecture Artificial Intelligence Business Analysis DAMA & Professional Development Databases & Database Design Database Administration Data Governance & Stewardship Data Management Data Modeling Data Movement & Integration Data Quality Management Data Security Management Data Warehousing & Business Intelligence Document, Record & Content Management Finance & Accounting Geospatial Data Knowledge Management Marketing & Customer Relationship Management Meta-Data Management Multi-dimensional & OLAP Normalization Object-Orientation Parallel Database Processing Planning Process Management Project Management Reference & Master Data Management Semantic Modeling Software Development Standards Organizations Structured Query Language (SQL) XML Development
Author | : Alfred Wittmann |
Publisher | : |
Total Pages | : 359 |
Release | : 1992 |
Genre | : EDB |
ISBN | : 9783486217377 |
Author | : James W. Cortada |
Publisher | : Greenwood |
Total Pages | : 0 |
Release | : 1987-06-23 |
Genre | : Education |
ISBN | : 0313256527 |
Product information not available.
Author | : Dama International |
Publisher | : |
Total Pages | : 628 |
Release | : 2017 |
Genre | : Database management |
ISBN | : 9781634622349 |
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.