Peter Aiken – författare

This text on data warehouse engineering takes readers from the planning and modelling stages right through to the implementation. It includes chapters on how to convert data from a legacy system to a modern data warehouse.

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.- 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

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.

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

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, and Reports 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

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, and- Reports 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