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DQ Blog Data Quality Good v Bad Data Quality

Good v Bad Data Quality

Martin Doyle January 19th, 2012 Data Quality

Good content is data which is fit for purpose.  It should be:

  1. Correct – present a Single Customer View (SCV)
  2. Complete – all the data you need is available
  3. Accurate – represents the truth
  4. Compliant – satisfies the rules imposed by the business
  5. Timely – available when you need it
  6. Duplicate free – accounts & contacts etc..
  7. Deliverable – have accurate addresses

Bad Content is when data is not fit for purpose. It causes:

  1. Wasted time – searching for data
  2. Wasted money – re-working incorrect data content
  3. Wasted energy which can be re-purposed for productive work
  4. Bad decisions due to lack of trust in data content
  5. Fraud going unnoticed
  6. Poor cash flow when invoices not delivered
  7. Postal deliveries to go to the wrong places
  8. Customer satisfaction to diminish
  9. Customer relationships to fail
  10. Customers to defect

At DQ Global® we know the difference between “Good” and “Bad” Data. Over the years we have worked with our clients to achieve their Data Quality goals. Please contact us if you would like our help with Data Deduplication, Address Verification, Data Cleansing, Record Matching for Single Customer View or any other Data Quality issues you may have.

Martin Doyle
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Written by Martin Doyle

Martin is CEO and founder of DQ Global, a Data Quality Software company based in the UK. With an engineering background, Martin previously ran a CRM Software business. He has gained a wealth of knowledge and experience over the years and has established himself as a Data Quality Improvement Evangelist and an industry expert.
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