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Mindmap

Unit One- Data, Information and Knowledge

turrc001 ICT Englisch

Inhalt der Mindmap

Unit One- Data, Information and Knowledge

  1. Data

    • Data is raw facts and figures with no meaning
    • Data can be alphanumeric, graphics or sound.
    • Data must be: Fit for purpose, accurate, not biased and up to date. (PABU)
    • Data put into meaningful orders using calculations or arrangements is processing.
  2. Information

    • Data + Context + Meaning=Information
    • Grouping or processing data by a computer makes it information.
    • Information is data which has been given meaning and context.
  3. Knowledge

    • Knowledge is application of information to a situation.
    • Knowledge is derived from information by applying rules to it.
  4. GIGO stands for Garbage In Garbage Out and it means when you put irrelevant data in, irrelevant data will come out and incorrect results will be made.

  5. Encoded Data

    • Encoded data is assigning codes to data to reduce their size.
    • Advantages
      • Easily transferable
      • Easy to back
      • Faster searching for data compared to typing in long codes
      • Increase accuracy of data entry
      • Coded data is quicker to type in
      • Takes up less storage space
    • Disadvantages
      • Training needed to learn the codes
      • Codes can be easily codes
      • Code may be confused-slow down code entry
      • Could run out of code combinations
      • May be entered incorrectly
  6. Data Validation

    • Data validation aims to make sure the data is sensible, reasonable, complete and within acceptable boundaries.
    • Validation is performed by the computer when you enter data. This process is called validation checks.
    • Data errors
      • Input errors-Type the wrong keys on a keyboard.
      • Transmission errors-Data is corrupted through the wires.
      • Transposition errors-Making an error by quickly typing and typing the letters in the wrong order.
      • Transcription errors-Transfer data from paper incorrectly or misheard data.
      • Processing errors-Making a mistake in writing mistakes in formulas on spreadsheets.
    • Validation checks
      • Range check-Used on numbers, currency and date/time. Checks to see if the data fits specific boundaries.
      • Data type check- will ensure data entered into the field is correct.
      • Presence check- checks that important data is stored and specific data is entered.
      • Format check- will check that the right characters and data types are entered.
      • Check digits- is used when you want to be sure if a range of numerical data has been entered correctly into a system.
  7. Data Verification

    • Data verification means to check that the data in the original source is the same as the data you have entered into the database.
    • Verification can be used to make sure that the data in your database contains as few errors as possible.
    • Verification checks
      • Visual check/Proof read: Carefully reading what has been entered and comparing it with the original data and change any mistakes.
      • Double entry: Typing the data in twice to make sure they are both the same and will only be accepted if they are.
      • Parity checking: Checks to make sure that the data sent is received from one computer to another and it has not corrupted.
      • Hash totals: Meaningless total of numbers such as order numbers to check all data has been entered.
      • Batch totals- A meaningful total of numbers that is used to check all the data has been entered into the computer.

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ICT Mindmap am Unit One- Data, Information and Knowledge, erstellt von turrc001 am 15/04/2013.
Erstellt von
turrc001
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