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AS Level ICT

AS Level ICT. Data entry: Problems with errors. Garbage in; Garbage out. If incorrect data is entered into a data management system, the results of any processing that takes place will be invalid Hence the use of the expression GIGO – ‘Garbage in; Garbage out’

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AS Level ICT

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  1. AS Level ICT Data entry: Problems with errors

  2. Garbage in; Garbage out • If incorrect data is entered into a data management system, the results of any processing that takes place will be invalid • Hence the use of the expression GIGO – ‘Garbage in; Garbage out’ • It therefore follows that it is a major concern for anyone who has to design and solve a problem to ensure that any data that is inputted into a data management system is correct

  3. Validity and correctness • For data to be valid, it must match certain rules • For example, if a field in a database is a numeric or number field, only numbers can be inputted into that field; letters would not be valid data for that field • However if the field – for example a field for client’s surnames – was an alphanumeric or text field (i.e. it can have both numbers and letters inputted into it) it would accept both Jones and J0nes as valid, even though only of one these entries is correct

  4. Validity and correctness • It follows, therefore that data must be both valid and correct (i.e. free from errors) • The number of errors can be reduced by the use of: • Verification • Validation

  5. Verification • Verification is the process of checking that the data entered into an ICT system matches the source of the data • For example, does the personal data someone has written on an application form for a job match the data that has been inputted by a keyboard operator into a data management system

  6. Verification • Two methods can be used to check data entered in such a way: • Proof reading • Double data entry

  7. Verification • Proof reading: This involves someone checking and matching each data entry visually – it is not fool-proof! • Double data entry: This involves two keyboard operators entering the same data, which is then compared and checked automatically to ensure that the data entries are identical – this is both expensive and not fool-proof (e.g. both keyboard operators might have made the same mistake)

  8. Verification • A further method of verifying data is to make the data entry process include a degree of self-checking • For example, individuals who are using the Internet to purchase items from an online retailer will have to complete an online order form and use some form of automatic payment system • Because they are entering their own personal details (e.g. name, address, postcode, credit card details) and because they are only making one data entry, they are less likely to make mistakes

  9. Verification • Furthermore, this will also save the online retailer money as they will not need to employ staff as keyboard operators do mundane data entries • Using such a system does not eliminate errors, but can go some way to reducing the number that occur

  10. Verification • The most common errors that occur are: • Transcription errors • Transposition errors

  11. Transcription errors • Transcription errors are errors that are made when data is being entered using documents or audio responses as the data source and a keyboard as the method of entry • The most common errors occur because of: • Problems understanding speech • Unusual spellings of words or names • Poor handwriting • Misinterpretation • Typing errors (typos)

  12. Transposition errors • Transposition errors are errors that are made when characters (i.e. letters and number) in data are entered in the wrong order • Examples of common transposition errors are: • Typing ‘form’ rather than ‘from’ • Reversing numbers in a sequence (e.g. ‘10078’ entered as ‘10087’) • Reversing letters in a sequence (e.g. ‘BD04NTJ’ entered as ‘DB04NTJ’)

  13. Verifying and validating content • Not all data used in ICT is entered into a data management system • For example, a website contains many different items of data, but is not a data management system • The data on the website still needs to be verified and validated, otherwise it cannot be trusted In particular, are their any types of websites that might contain unverified and invalidated data?

  14. Verifying and validating content • Examples of methods of verification and validation of the content of a website are: • Checking the accuracy of content against a variety of other sources (e.g. checking it against other online and available printed sources) • Checking the readability of the content (e.g. is it suitable for the audience?) • Spellchecking all text • Grammar checking all text

  15. Verifying and validating content • Examples of methods of verification and validation of the content of a website are: • Ensuring that images that should appear do appear – avoid the dreaded ‘x’ in a box! • Checking that all content is present – proof reading should ensure that missing text and images are spotted before the website is uploaded to the Internet • Ensuring that content is not duplicated – proof reading should also ensure that this problem is avoided

  16. Verifying and validating content • Examples of methods of verification and validation of the content of a website are: • Using standard or consistent layouts and colour schemes • Ensuring that images are the correct size and resolution – too large an image takes too long to download; if the image resolution is too low the image will be blurred and indistinct

  17. Verifying and validating content • Examples of methods of verification and validation of the content of a website are: • Ensuring that the font style and font size are appropriate for the audience • Checking that any images used are appropriate and suitable for use with the text they are used to illustrate

  18. AS Level ICT Data entry: Problems with errors

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