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Cleansing
After a data set successfully meets profiling standards, it still
requires
data cleansing and
deduplication to ensure that all
business rules are properly met. Successful data cleansing requires
the use of flexible, efficient techniques capable of handling
complex quality issues hidden in the depths of large data sets. Data
cleansing corrects errors and standardizes information that can
ultimately be leveraged for MDM applications.
Next Step: Parsing and Standardization
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