Peter Aiken – författare

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.

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:

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.

Pervasive, data is a unique organizational resource, and this distinction warrants its own strategy. Data, representing your single non-depletable, non-degradable, durable strategic asset, is likely also your most poorly leveraged and underutilized organizational asset.Lack of talent, barriers in organizational thinking, and seven specific data sins prevent most organizations from benefiting fully from their data asset investments. Solving these prerequisites will allow your organization to:• Improve your organization’s data;• Improve the way your people use data; and• Improve the way your people use data to achieve your organizational strategy.This method better focuses data and thinking in direct support of strategic objectives. After eliminating necessary prerequisites, organizations can develop a disciplined and repeatable means of improving their data, literacy, standards, and controls using data governance practices. Once in place, the process (based on the theory of constraints) becomes a variant of lather, rinse, and repeat. Several complementary concepts covered include:• An overview of data strategy prerequisites;• A repeatable process for identifying and removing data constraints;• Why data strategy is necessary for effective data governance;• Balancing operational results with capability development;• An objective definition of data-centric thinking; and• Ways to monetize these efforts.