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: <ul>
<li>Dedication solely to leveraging data assets,</li>
<li>Unconstrained by an IT project mindset, and</li>
<li>Reports directly to the business</li>
</ul>
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.

The Case for the Chief Data Officer: Recasting the C-Suite to Leverage Your Most Valuable Asset

Business & Money

Aiken, Peter

Gorman, Michael M.

Management & Leadership

Morgan Kaufmann

Computing Fundamentals: Microsoft Word 5.0

Computers & Technology

Haggard, Gary

Software

Addison-Wesley

Describes techniques essential to implement an enterprise database—a network of databases across various computing platforms. Explains how to define the enterprise data model, the principles and methodology necessary to characterize the database project environment and enterprise database projects that lead to success. Concludes with a summary of the entire database effort.

Enterprise Database in a Client/Server Environment

Networking & Cloud Computing

*A Wiley-QED Publication

Managing Data Base: Four Critical Factors

Q E D Pub Co

Enterprise Database in a Client-Server Environment

QED Information Sciences

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

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

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

See the best price to sell, buy, or rent books by Gorman, Michael M.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Gorman, Michael M.

See the best price to sell, buy, or rent books by Gorman, Michael M.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

The Case for the Chief Data Officer: Recasting the C-Suite to Leverage Your Most Valuable Asset

Computing Fundamentals: Microsoft Word 5.0

Enterprise Database in a Client/Server Environment

Managing Data Base: Four Critical Factors

Enterprise Database in a Client-Server Environment

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