Developers
Corner
 Don’t
Lose Faith in Data Quality
Businessmen and IT specialists don’t seem to have
much faith in data quality. According to a recent
study by TDWI, a data warehousing and business
intelligence firm, about 82.5 percent see their data
is “good or okay.” But nearly 50 percent of those
surveyed say their data quality is “worse than
everyone thinks.”
This is why many companies erected a data quality
plan to combat the problem, the report reveals. The
survey also reveals that 53 percent of respondents
say they’ve suffered losses, problems and costs due
to shoddy data quality. Two-thirds of respondents
have studied the problems of data quality, while
less than half have studied what’s good about it.
As a result, the report notes, this shows that data
quality initiatives are driven more by liability
than leverage. Organizations validate their data to
avoid problems like direct mail costs, misguided
decisions, poor customer service, faulty information
in financial and regulatory reports, the survey
notes.
Why is data quality so hard to grasp? Apparently
because data quality is a very complex concept that
incorporates many different technologies and
business practices. As a result, many misconceptions
about data quality flourish. One of the
misconceptions is that data quality can be achieved
with a one-time action that results in perfection.
Not so, says the report. Data quality is applied
consistently over time as the state of quality
evolves.
The survey also revealed that data quality products
and practices are also evolving and changing with
the times – moving from technical and business
users, from point products to suites, from batch to
real-time operation, from data profiling to quality
monitoring, from being domestic to more global, etc.
“All these trends boil down to the fact that data
quality is broadening beyond its departmental roots
into enterprise-scope usage. While this broadening
is good for the data, it’s challenging for the
organization, which must adjust its business
processes and IT org chart to adapt to enterprise
usage,” the report notes.
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