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Validation and Verification
What is validation? Name 5 types of validation What is verification? Give an example to illustrate the difference between validation and verification. Learning objectives with a TWIST
A method of checking data as it is entered, to reduce the number of errors. A Validation Rule is what the data is tested against. If the data fails to meet the criteria an error message will appear. Validation
Presence check – has the data been entered Range check – is the data within a certain range of letters or numbers? E.g. 1-99 Format check – does the data follow a correct pattern e.g. DOB 18/02/1981 Length check – Has the correct number of characters been entered? List/Lookup check – Is the data within the list of acceptable values? Cross Field check – Checks two fields are entered correctly e.g. if a particular phone is available on only one network it will be rejected if a different network is selected Check digit – Make sure longer numbers are entered correctly e.g. barcode (last digit checks via complex calculation that the previous digits are correct) Validation Types
Validation reduces data entry errors but can not remove them completely Example: 18/02/1991 might be entered instead of 18/02/1981 The above meets the validation rule (format) but is obviously wrong which might mean that the system rejects the customers application (e.g. would be to young to get a phone contract) To avoid this we use verification Validation Continued
Is the process of proofing the data  This can be done by proofreading or double data entry  (two pass verification) Double data entry  is where the data is entered twice systematically and then verified to make sure both entries are the same Verification

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Validate Verify Data Entry Errors

  • 2. What is validation? Name 5 types of validation What is verification? Give an example to illustrate the difference between validation and verification. Learning objectives with a TWIST
  • 3. A method of checking data as it is entered, to reduce the number of errors. A Validation Rule is what the data is tested against. If the data fails to meet the criteria an error message will appear. Validation
  • 4. Presence check – has the data been entered Range check – is the data within a certain range of letters or numbers? E.g. 1-99 Format check – does the data follow a correct pattern e.g. DOB 18/02/1981 Length check – Has the correct number of characters been entered? List/Lookup check – Is the data within the list of acceptable values? Cross Field check – Checks two fields are entered correctly e.g. if a particular phone is available on only one network it will be rejected if a different network is selected Check digit – Make sure longer numbers are entered correctly e.g. barcode (last digit checks via complex calculation that the previous digits are correct) Validation Types
  • 5. Validation reduces data entry errors but can not remove them completely Example: 18/02/1991 might be entered instead of 18/02/1981 The above meets the validation rule (format) but is obviously wrong which might mean that the system rejects the customers application (e.g. would be to young to get a phone contract) To avoid this we use verification Validation Continued
  • 6. Is the process of proofing the data This can be done by proofreading or double data entry (two pass verification) Double data entry is where the data is entered twice systematically and then verified to make sure both entries are the same Verification