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Poor data quality can be mitigated much more easily if caught before it is used — at its point of origin. If you
verify or standardize data at the point of entry, before it makes it into your back-end systems, we can say that it
costs about $1 to standardize it. If you cleanse that data later, going through the match and cleanse in all the
different places, then it would cost $10 in comparison to the first dollar in terms of time and effort expended.

And just leaving that bad quality data to sit in your system and continually give you degraded information to
make decisions on, or to send out to customers, or present to your company, would cost you $100 compared to the $1 it would’ve cost to actually deal with that data at the point of entry, before it gets in. The cost gets greater the longer bad data sits in the system.


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