GCSE ICT

1
GCSE ICT

• LESSON 5
• Booklet Sections 6 7
• Data Capture Checking Data

2
What is data?

• Data is raw facts and figures.
• In order to process data it has to be collected.
• The method of collecting data depends upon what
  it is going to be used for.

3
Designing a data capture sheet

• The process of collecting data is called DATA
  CAPTURE.
• If a printed form is used to collect data it is
  called a DATA CAPTURE SHEET.

4
Designing a data capture sheet

• The design of a data capture sheet should help
  the user to collect data efficiently and
  accurately.
• It should also enable the data to be entered into
  a database efficiently and accurately.

5
Designing a data capture sheet

• A good design will have

• Informative headings.
• Simple instructions.
• An easy to use layout.
• Logical divisions into sections.
• Been tested before use.

6
An example of a data capture sheet

• Informative headings.
• Simple instructions.
• An easy to use layout.
• Logical divisions into sections.

Personal data
Academic data
7
Questions

• Data capture is about getting the answers to
  specific questions.
• There are two types of question.
• These are
• Closed questions
• Open-ended questions

8
Closed questions

• Closed questions are the easiest to answer and
  easiest to process.
• Closed questions can produce
• Yes/No or True/False answers.

9
Open-ended questions

• Open-ended questions are the more difficult to
  answer and less easy to process.
• This is because the answers are open-ended
  (i.e. they allow users to enter any answers they
  wish).

10
Examples of closed and open-ended questions

• Closed questions
• Open-ended questions

Only grades from A to U can be entered
Only percentages can be entered
Written comments can be added
11
Coding data

• Because closed questions only allow users to
  enter answers from a specific list of
  alternatives it is easy to encode the data before
  entering it into a database.

12
Coding data

• For example, examination grades can be entered a
  single letters (A, B, C, D, E, F, or U).
• Another example is gender, which can be entered
  as M (for male) or F (for female).
• Individuals can also be given their own code
  number to identify them (e.g. National Insurance
  Number).

13
Coding data

• Why use codes?

• They are quicker to enter.
• It reduces the size of computer files, which
  increases the speed at which data can be handled.
• Codes can be unique.

14
Entering data into a database

• Once data has been captured, it will need to be
  entered into a database.
• This can be done by a variety of methods
  including
• Keying in using a keyboard
• Magnetic Ink Character Recognition (MICR)
• Optical Mark Reading (OMR)

15
Entering data into a database

• This can also be done by
• Optical Character Recognition (OCR)
• Barcode readers
• Automatic data capture
• Turnaround documents

16
Keying in data

• This is the most common form of data entry as it
  is flexible and can cope with different types of
  data.
• However it is time consuming and errors can occur
  very easily.

17
Automatic data capture

• Some data can be entered directly into a database
  by electronic signals.
• Examples of automatic data capture include
• EPOS (Electronic Point Of Sale)
• Remote sensing of traffic flow

18
Why do errors happen?

• Computers do not make mistakes.
• However if incorrect data is put in errors
  happen.
• In ICT this is called GIGO Garbage in, garbage
  out!
• The way to avoid incorrect data being entered is
  to check it thoroughly.

19
Checking Data

• There are two main methods of avoiding errors.
• These are
• Verification
• Validation

20
Verification

• Verification is the process of checking data.
• This can be done visually by the person entering
  the data.
• This can be done by double data entry (i.e. two
  people enter the same data, and if it is
  identical the data is accepted).

21
Validation

• Validation is the process of detecting
  inaccurate, incomplete, or unreasonable data.
• This can be done by the computer as the data is
  entered and as a result it is much less likely
  that errors will occur.

22
Ways to Validate Data

• These include

• Character type checks
• Range checks
• Presence checks
• Length checks
• Lookup tables
• Spelling checkers

23
Validation

• Others include

• Hash totals
• Control total
• Check digits
• Custom dictionaries
• Parity errors

24
Character type checks

• Character type checks make sure that the correct
  type of character has been entered (e.g. that a
  number has not been entered where a letter should
  have been or that a letter have not been entered
  where a number should have been.

25
Range checks

• Range checks make sure that numerical data falls
  between pre-determined limits (i.e. within a
  certain range of numbers).
• For example, that the age of a pensioner who is a
  member of a pension scheme and who is 81 is not
  entered as 18.
• This is done by setting a bottom limit on the age
  range.

26
Range checks

• Range checks are not infallible.
• In the example of the pension scheme data, if the
  age of the pensioner had been 96 and it had been
  entered as 69, the mistake would not have been
  detected by a range check.

27
Presence checks

• Presence checks ensure that data that must be
  entered is entered.
• For example, the pension scheme would need a
  pensioners National Insurance number.
• If that was not entered the presence check would
  detect this and notify whoever was entering the
  data.

28
Length checks

• Certain types of data are always the same length.
• For example, a National Insurance number will
  have 2 letters, followed by 6 numbers, followed
  by 1 letter (e.g. YY232425A).
• A length check will identify any NI numbers that
  have more or fewer characters.

29
Lookup tables

• A lookup table contains a list of valid codes
  that can be used to enter data.
• If a code that is not in the lookup table is
  entered. it is rejected.
• This prevents any incorrect data from being
  processed.

30
Spelling checkers

• Although spellcheckers are usually found in word
  processing programs, they can also form part of
  data-handling programs.
• They can be enabled (switched on) so that they
  check data as it is entered and automatically
  identify any mistakes.

31
Custom dictionaries

• If a spellchecker is used it will automatically
  identify any words that it does not recognise.
• In particular spellcheckers often fail to
  recognise proper names (i.e. the names of people
  or places) or specialist words or jargon.

32
Common errors

• Common types of error are
• Transcription errors these usually occur when
  people entering data misread what they are
  entering (e.g. mistaking 5 for S or O for 0).
• Transposition errors these occur when people
  entering data get characters out of order or back
  to front (e.g. 619 instead of 916 or form
  instead of from).