A Framework for Classifying Data - High-Performance Web Databases: Design, Development, and Deployment - page 72

new technology. The major subjects and their subtypes of customer have
such attributes as:
• address
• age
• salary
• occupation
• number of dependents
The major subjects and their subtypes of competition have such
attributes as
• market share
• product line
• length of time in business
The major subjects and their subtypes of new technology have such
attributes as
• description
• developer
• potential uses
Not only are the attributes fewer and less stable, but the major subject
areas in this quadrant are constantly changing. The gathering, use, and
content of data in this quadrant are very different from those of data in
other quadrants.
Other Dissimilarities
The dissimilarities of data from one quadrant to the next are not limited
to the differences between the external administrative and the external
directional quadrants. They extend to the representation of data from the
external administrative and the internal directional quadrants. The data in
the external administrative quadrant represents such tangible objects as
shipments, products, parts, and customers. In addition, there are less eligi-
ble entities that have a legal and logical form, if not a physically tangible
form. These include bank accounts, insurance claims, and financial trans-
actions. In short, the external directional quadrant contains data that mea-
sures tangible objects.
In contrast to this, the objects represented in the internal directional
quadrant tend to be intangible. Such data as objectives, goals, and motiva-
tions are found in this quadrant. The amorphous nature of these objects is
reflected in the difficulty of trying to assign significant keys, attributes, and
relationships to the data model representing them.
The very different nature of data in the various quadrants can also be
seen from the perspective of the audience served by them. Some overlap