The Data Interoperability Community of Interest Handbook provides the: * Rationale for Shared Data Environments across the Enterprise * Blueprint for Collaborative Data Sharing * Why Communities of Interest are Ideal Organizational Structures * How Communities of Interest are Best Engineered * Step-by-Step Strategies to Build Common Data Architectures * Methodology &amp; Plan to Create Focused Organizations * Strategies for Meetings, Decision Making, and Voting * And Much, Much More!

Data Interoperability Community of Interest Handbook

Computers & Technology

Gorman, Michael M.

Databases & Big Data

Whitemarsh Information Systems Corporation

It is common for information systems development projects to be late, exceed budget projections, and contain significantly fewer features than proposed. This book provides a strategy whereby these problems can be resolved. This strategy is based on techniques and methods that have been proven over 30+ years. This book is based on data-driven requirements strategy, and the use of prototyping to evolve the business information system's design until all the fundamental requirements have surfaced, been tested, and been agreed to by users. Then and only then can implementation proceed. The production system can directly proceed from the prototype. All the techniques in the book are based on a real metadata repository and a business information system generator. Screen shots from both are included.

Strategy for Successful Development of Information Systems

Computer Science

Enterprises grow, stagnate, or even die by the quality of their archtiectures. May businesses have inappropriate or even wrong information systems technology because these technologies are not properly engineered. The first step is to understand that many businesses are built on the knowledge worker. A framework for the knowledge worker is important. Within this framework exists five critical architectures: the Enterprise's Archiecture, the Database Objects Archtiecture, the Data Architecture, the Resource Life Cycle Architecture, and the Information Systems Planning Architecture. These five architectures overlap and are interlinked. If the work products created for these architectures stand alone, much time and resources will have been wasted. A Metadata management systems is critical to interrelate these architectures thus making their work products non redundant. Properly engineered, these architectures enable the enterprise to thrive and to be able to change in the face of business adversity and changing technologies. This books sets out the five architectures, shows the interrelationships among all the work products and describes the metadata repository system needed to be successful.

Enterprise Architectures

Business & Money

Management & Leadership

The Data Interoperability Community of Interest Handbook provides the: * Rationale for Shared Data Environments across the Enterprise * The Unbeatable Business Case * Blueprint for Collaborative Data Sharing * Why Communities of Interest are Ideal Organizational Structures * How Communities of Interest are Best Engineered * Step-by-Step Strategies to Build Common Data Architectures * Methodology & Plan to Create Focused Organizations * Strategies for Meetings, Decision Making, and Voting * And Much, Much More!

The Data Semantics Management book is divided into two volumes. Volume 1, this volume, addresses Rationale, Requirements, and Architecture. Volume 2 addresses Deployment. This volume justifies why accomplishing data semantics management is so critical to the overall success of data interoperability and shared data. The approach embraced by these two volumes is founded on the idea of top-down and centralized architecture, engineering, policies, and procedures, but bottom-up, distributed accomplishment. If attempted only top-down, the outcomes will mirror familiar centralized czar-like failures of the past. If accomplished only bottom-up, the outcomes will be the vast forests of semantic stove pipes. Volume 1 presents these key topics: Rationale, Data Semantics Components, Failures and Lessons Learned, Engineering, Successful Name Construction, Semantic Hierarchies including taxonomies and ontologies, Value Domain Managememnt, and the Business Fact Specification cases including Business Rule engineering. The book identifies and describes the two error classes that prevent data interoperability and sharing. Each chapter addresses how these two classes are addressed. Each chapter concludes with an extensive set of questions and exercises.

Data Semantics Management, Volume 1, Rationale, Requirements, and Architecture

The Data Semantics Management book is divided into two volumes. Volume 2, this volume, addresses Deployment. Volume 1 addresses Rationale, Requirements, and Architecture. The approach embraced by these two volumes is founded on the idea of top-down and centralized architecture, engineering, policies, and procedures, but bottom-up, distributed accomplishment. If attempted only top-down, the outcomes will mirror familiar centralized czar-like failures of the past. If accomplished only bottom-up, the outcomes will be the vast forests of semantic stove pipes. Volume 2 presents these key topics: Data element architecture and engineering via the ISO Standard 11179; development of data models of concepts to be used as templates for manufacturing database data models; the development of "logical" data models from concept data model templates; the development of "physical" data models from one or more "logical" data models; the engineering of view data models including generation of XML schemas and Service Oriented Architecture (SOA); Database object class models that includes data structure, process, and state; work plans for accomplishing data semantics management within a project, organization, function, and enterprise; and an overall two-volume summary including a chapter by chapter explanation of how the two interoperability and shared data error classes have been eliminated or severely reduced. Each chapter concludes with an extensive set of questions and exercises.

Data Semantics Management, Volume 2, Deployment

Concepts and terms are critical to a clear understanding of any complex subject. Data management, database, enterprise database, and business information systems are such subjects and they use a dizzying quantity of terms and concepts. Some that are the same mean different things. Some that are different mean the same thing. This book, Concepts and Terms, comprehensively provides, defines, and illustrates uses of over 900 terms and concepts that critical to data management, database, enterprise database, ANSI Database Standards, DBMS Standards including SQL, and business information systems. This book also serves as the one-book concepts and terms source for all the Whitemarsh Information Systems Corporation data management product line.

Data Management's Concepts & Terms

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Books by Whitemarsh Information Systems Corporation

See the best price to sell, buy or rent books by the Whitemarsh Information Systems Corporation publisher. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Data Interoperability Community of Interest Handbook

Strategy for Successful Development of Information Systems

Enterprise Architectures

Data Interoperability Community of Interest Handbook

Data Semantics Management, Volume 1, Rationale, Requirements, and Architecture

Data Semantics Management, Volume 2, Deployment

Data Management's Concepts & Terms