Page 246 - DCAP603_DATAWARE_HOUSING_AND_DATAMINING

Data Warehousing and Data Mining

notes In addition, Trans Union was able to identify vehicles by type, classify each vehicle in
a standardized, format and create and append new vehicle classifications to the original
records.
“Training and learning the Trillium Software System occurred much more easily and
quickly than we had imagined. We were able to set up the tables and learn how to tune
them within one week, and that allowed us to go live immediately,” said the team leader.
Because the implementation was so quick and easy, Trans Union is now considering
adding more categories to the mix of products being mined from its consumer database.
The company has demonstrated once again that clean data provides a more accurate view
of consumers and delivers a more valuable product for its clients.

12.5 summary

l z DWQ provides the framework and modeling formalisms for DW design, development
and maintenance tools that can be tuned to particular application domains and levels of
quality.

l z The potential of such an approach has been demonstrated already by successful commercial
usage of the ConceptBase metamodeling tool developed in the COMPULOG project.

l z DW development time for a given level of quality will be significantly reduced and
adaptation to changing user demands will be facilitated.
l z There is a high demand for design tools for distributed databases which is not satisfied by
current products.
l z DWQ has the potential to satisfy this demand for an increasingly important market
segment.

l z In addition, a host of quality-enhanced query and update services can be derived from
DWQ results.
l z Prototypes of specific models and tools developed in the project will be experimented
with in various industry and public administration settings, in order to gain reference
experiences for industrial uptake of project results.

12.6 keywords

Data Warehouse Quality: In the DWQ (Data Warehouse Quality) project we have advocated
the need for enriched metadata facilities for the exploitation of the knowledge collected in a data
warehouse.
Information Quality: Information quality is the key to political success.

Technical Quality: Technical quality is the ability of the data warehouse to satisfy users’ dynamic
information needs.
The Metadata Hub: The meta data hub is used for managing the interchange and sharing of
technical meta data between decision processing products.

240 LoveLy professionaL university