UNIT 1: TOPIC 1: Data and Quality of Data

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Mind Map on UNIT 1: TOPIC 1: Data and Quality of Data, created by tangj024 on 04/15/2013.
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Mind Map by tangj024, updated more than 1 year ago
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Resource summary

UNIT 1: TOPIC 1: Data and Quality of Data
  1. Keywords and Definitions
    1. GIGO: Abbreviation for garbage in garbage out. It means if you out rubbish into the computer then you get rubbish out.
      1. DATA: Raw facts and figures, e.g. readings from sensors and survey facts, etc. Data can be numbers, words, images, sound.
        1. Processing: Performing calculations or arranging the data into a meaningful order. Example would be working out an athlete’s average age over 3 years.
          1. Transaction: A piece of business, e.g. an order, purchase, return, delivery, transfer of money etc. An example would be buying clothes online.
            1. Information: Data that has been processed by the computer. Data + Meaning + Context = Information
              1. Knowledge: Derived from information by applying rules to it. Example would be we can see an increase in the athlete’s wages.
              2. Encoding
                1. Encoding: Assigning codes to the data reducing its size.
                  1. Advantage
                    1. Advantages of encoding: takes up less storage space, easily transferable, easier to back.
                    2. Disadvantage
                      1. Disadvantages of encoding: Easily stolen, training needed, security problem, viruses etc.
                      2. Examples:
                        1. Two examples would be: 1. Size of clothes- S= Small, M= Medium, L= Large 2. Airport codes- LHR= London Heathrow, MAN= Manchester
                    3. Data Validation
                      1. Transcription error: Error made when typing in data using a document as the source of the data.
                        1. Examples:
                          1. Example mishearing what a person says over the telephone and entering it into the computer.
                        2. Transposition error: Error made when characters are swapped around so they are in the wrong order.
                          1. Examples:
                            1. Example would be putting faceboko instead of facebook.
                          2. Check digit: A decimal or alphanumeric added to a number for the purpose of detecting the sorts of errors humans normally make on data entry.
                            1. Examples:
                              1. Example account numbers will have check digits, to check that the numbers inputted are correct.
                            2. Range check: Data validation technique which checks that the data input to a computer is within a certain range.
                              1. Examples:
                                1. Checking the data of birth of a yr 9 pupil, if DOB is lower than 1998, the system wouldn't allow that person to enter that date as they are too old.
                              2. Presence check: Is used to check that data is entered into the correct fields.
                                1. Examples:
                                  1. For example entering your username and password on facebook.
                                2. Validation checks: Are checks a developer of a solution sets/ creates, using the software, in order to reduce errors.
                                  1. Examples:
                                    1. Presence and range checks are validation check examples.
                                3. Data Verification
                                  1. Batch total: A meaningful total that is used to check that the computer has input all the data.
                                    1. Examples:
                                      1. For example adding up all the totals of a batch of sold ebay items.
                                    2. Hash total: Meaningless total of numbers, such as order numbers, used to check that all the data has been entered.
                                      1. Parity check: Check to make sure that the data sent is the same as that received when data is transmitted from one computer to another.
                                        1. Examples:
                                          1. An example would be an email sent from one person to another.
                                        2. Verification: Checking that the data being entered into the ICT system perfectly matches the source of the data.
                                          1. Examples:
                                            1. An example would be checking the text/ data in an email and making sure when it arrives to the recipient that no error have been introduced.
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