|
|
|
Data Quality Tools—Not a “One-Size-Fits-All” Solution High quality data is critical to business success. Yet unreliable, outdated, or
just plain inaccurate data costs U.S. businesses more than $600 billion
annually.
Data quality is the starting point for most marketing projects. You can’t
achieve successful results with inadequate, incomplete, or incorrect data. Data
quality tools can enhance the quality of your contact data for direct mail,
target marketing, address verification, and data-driven initiatives.
Understanding the key data quality dimensions is the first step to data quality
improvement. Being able to segregate data flaws by dimension or classification
allows analysts and developers to apply improvement techniques using data
quality tools to improve both your information and the processes that create and
manipulate that information.
Organizations rely on data quality tools to ensure contact records are complete
and accurate – and prevent fraud and waste associated with bad contact data.
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 domestic to global, APIs, etc.
Data quality is not a “one-size-fits-all” solution. Achieving data quality is
not an all or nothing project. Data quality management is an ongoing process
that should be applied consistently over the lifetime of the data.
To find more news and information about data quality solutions, turn to
your partner in data
quality.
|
|
|
|
