Data Management - The CIO's Guide to Oracle Products and Solutions - page 188

Data cleansing standardizes data according to specifically defined rules;
eliminates redundancy to increase data-query accuracy; reduces the cost
associated with inaccurate, incomplete, and redundant data; and reduces
the risk of invalid decisions made against incorrect data.
Good Data Management Practices
Data management is an integral function in most large organizations. It
must be rigorously performed and maintained. The rapid and expansive
development of information management technologies has opened the
door to a vast world of information that can be processed and analyzed
with increasing speed and complexity. Ensuring that information (and the
interpretations derived from it) is accurate is the key challenge for success-
ful data management. Sound data management involves a series of actions
that must be clearly defined, clearly understood, and diligently followed.
The achievement and maintenance of data integrity depend on several
key data management roles within the organization: data/project spon-
sors, data stewards, data and database administrators, and system admin-
istrators. Each of these roles is discussed in the following section.
Data Management Roles
Table 6.3 displays the relationship matrix between data management
functions and personnel's corresponding roles. It is quite possible for roles
to require both content knowledge and technical skills. As we move across
the matrix from data sponsorship to system administration, the required
skills gradually shift from content in nature (program management level,
data-content level) to more highly technical in nature (systems, database
management, GIS skills, etc.).
Each of these roles is described in the following subsections.
Data Sponsor
The data sponsor is an advocate for a particular information activity such
as a spatial data set or application. The person in the organization rep-
resenting this role has a vested interest in the information activity and
provides an appropriate level of support to ensure its success. The data
sponsor normally has decision authority (at the management level) and
approves resources available to the project.