The Data Asset: How Smart Companies Govern Their Data for Business Success

Tony Fisher







Reviewed by

Mehmet Hurer MBCS CITP CEng


9 out of 10

The Data AssetIf you ever need evidence as to why data and its quality is so important to an organisation, or need to convince others, Tony Fisher’s book is an excellent place to start.

The book is split logically into four sections: the business case for data governance, the data governance maturity model, utilising people and processes to achieve data quality culture, and the use of the right technology, with clearly explained transition from one section to the next.

In section one, the author explains how critical good quality data is for an organisation.

Examples are provided throughout to illustrate the point, including organisations that cannot provide a single view of their customers, failure of CRM and ERM projects due to inconsistent and incomplete data, and why mergers and acquisitions often fail to achieve their expected business benefits due to an inconsistent understanding of their respective customers.

Once the problems have been presented the author provides guidance on how such issues could have been resolved by, for example, using technology such as data cleansing and matching.

Building on this, in section two the author presents the data governance maturity model, which is a framework and road map to achieving and maintaining good quality data. Again, this is reinforced with the business benefits associated with moving up the maturity model, such as the ability to automate business processes.

Section three focuses on the type of people and expected culture, covering the roles of all employees in an organisation, as well as specific data quality associated roles, such as data stewards and business data experts. Also discussed in this section is process, i.e. a data management life cycle, with five stages, each of which are presented in sufficient detail, including who should and should not be involved in the process as well as reiterating the point that this is an ongoing continuous activity and not a one-off project.

The final section discusses the types of tools available, which are presented in the context of where an organisation sits within the maturity model. So, for example, an organisation which has yet to achieve consistently good data quality may use data analysis tools that look for duplicate data or data within invalid ranges.

Overall, a well-presented and well-illustrated book, suitable for all level of readers.

Further information: Wiley

December 2009