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: Dedication solely to leveraging data assets, Unconstrained by an IT project mindset, andReports directly to the business

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.
Uncovers that almost all organizations need sophisticated, comprehensive data management education and strategies.Delivery of organization-wide data success requires a highly focused, full time Chief Data Officer.Engineers organization-wide data advantage which enables success in the marketplace

Whats the Return on Investment (ROI) on data management? Sound like an impossible question to answer? Not if you read this book and learn the value-added approach to managing enterprise resources and assets. This book defines the five interrelated best practices that comprise data management, and shows you how by example to successfully communicate data management ROI to senior management. The 17 cases we share will help you to identify opportunities to introduce data management into the strategic conversations that occur in the C-suite. You will gain a new perspective regarding the stewardship of your data assets and insulate your operations from the chaos, losses and risks that result from traditional approaches to technological projects. And you will learn how to protect yourself from legal challenges resulting from out-sourced information technology projects gone badly due to incorrect project sequencing and focus. With the emerging acceptance and adoption of revised performance standards, your organisation will be better prepared to face the coming big data deluge! The book contains four chapters: Chapter 1 gives a somewhat unique perspective to the practice of leveraging data. We describe the motivations and delineate the specific challenges preventing most organisations from making substantial progress in this area; Chapter 2 presents 11 cases where leveraging data has produced positive financial results that can be presented in language of immediate interest to C-level executives. To the degree possible, we have quantified the effect that data management has had in terms that will be meaningful to them also; Chapter 3 describes five instances taken from the authors' experiences with various governmental defence departments. The lessons in this section however can be equally applied to many non-profit and non-defence governmental organisations; Chapter 4 speaks specifically to the interaction of data management practices, in terms of both information technology projects and legal responsibilities. Reading it can help your organisation to avoid a number of perils, stay out of court and better vet contractors, experts and other helpers who play a role in organisation information technology development.

XML in Data Management is for IT managers and technical staff involved in the creation, administration, or maintenance of a data management infrastructure that includes XML. For most IT staff, XML is either just a buzzword that is ignored or a silver bullet to be used in every nook and cranny of their organization. The truth is in between the two. This book provides the guidance necessary for data managers to make measured decisions about XML within their organizations. Readers will understand the uses of XML, its component architecture, its strategic implications, and how these apply to data management.
To view a sample chapter and read the Foreword by Thomas C. Redman, visit http: //books.elsevier.com/mk/?isbn=0120455994
* Takes a data-centric view of XML.
* Explains how, when, and why to apply XML to data management systems.
* Covers XML component architecture, data engineering, frameworks, metadata, legacy systems, and more.
* Discusses the various strengths and weaknesses of XML technologies in the context of organizational data management and integration.