tered since 2001 must be in the database is accomplished with 100% precision
by data source A, and 99% precision by data source B.
??? Data.source.quality.assessment: The goal of this step is the integration, in
a single data source assessment matrix, of the three essential components of
the methodology: (a) data requirements; (b) quality requirements; and (c) data
sources. The output of the process is, for each data element, the best data source
for obtaining it, and a range with the qualification for each data source. The
Global Data Source Performance is computed, using a procedure that adapts
the QFD methodology.
Example.5:.The data source quality assessment matrix for our running
case study is depicted in Figure 2. We only show the data element ???sales???
and two queries: Q1 (from user U2) and Q4 (from user U3). The information
gathered so far is:
a. Query Q1
. Priorities. of. quality. dimensions:. accuracy:. 5, consistency: 4,
completeness: 3, timeliness: 5.
Global priority of the query: 135 (as explained in Phase III).
. Aggregations.required: month and salesman.
b. Query Q4
. Priorities.of.quality.dimensions: accuracy: 4, consistency: 5, completeness:
1, timeliness: 3.
Global priority of the query: 31
. Aggregations.required:.Country, province, city, neighborhood.
Finally, the data producer user provided the following information:
Available data sources: A, B, and C (c in Figure 2), with priorities
5,4,1 respectively, as explained previously (b in Figure 2).
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