Data Verification

There are typical errors experienced when doing data entry like transcription errors and transposition errors.

Transcription Errors

Every time data is manually entered into the system there is a possibility that an error will be committed.
Human errors do occur and there are different reasons why they happen. Long codes that have no significant meaning to the encoder are susceptible to error.
An example of a transcription error might be entering ‘fate’ instead of ‘faith’.

Transposition Errors

Transposition errors happen when the encoder accidentally switched the order of numbers or letters.
For example, 78 might be entered as 87 or ‘faith’ might be entered as ‘faiht’.

Verification

Validation cannot make sure that the data that you enter is correct, it can only check that it is rational, logical and acceptable.  Still, it is essential to have as much as possible an accurate information in your database.
Verification can be done to ensure that the data in the database has very minimal errors as possible.  Verification is done to make sure that the data entered is equal to the data from the original source.
Verification means to check that the data from the original source document is exactly the same as the data that you have entered into the system.

Methods of Verification

  • Double entry – This means inputting the data twice and comparing the two entries.
    • A classic example would be when creating a new password.  You are often asked to enter the password twice.  This lets the computer verify that data entry is exactly the same for both instances and no error has been committed.  The first entry is verified against the second entry by matching them.
    • While this may be useful in identifying many errors, it is not practical for large amounts of data.  Here are some disadvantages of double entry:
      • It would take an encoder a lot of time to input the data twice.  It doubles the workload as well as the cost.
      • An encoder could input the same error twice and, so it wouldn’t be traced as an error.
      • There’s a possibility of having two versions of data.
  • Proofreading data – This process requires another person checking the data entry against the original document.  This is also tedious and costly.
  • Checking the data on the screen against the original paper document – It can help identify transcription and transposition errors.  It also saves time from doing double entry.  Though, it is difficult to keep shifting your eyes back and forth from the monitor to the hard copy.  Also, human factors like tiredness and blurry eyes can result to missed errors.
  • Printing out a copy of the data and comparing the printout to the original paper document– This is probably the simplest way of verification because you can put both copies side by side and scan both for errors.  However, it can be tedious if there is a big amount of data to check.  Also, if scanned too quickly, errors could be overlooked.
  • Getting a helping hand– If you will verify data with a team member, then a good way of identifying errors is for the coworker to read the input data while you check it against the original document.  This can consume a lot of time and it utilises two people, so it depends on how crucial the data is to spend time and resources.  It is recommended that the second person will read the input data instead of yourself, because there is a high possibility that you will commit the same mistake twice like transposing a number.