Data and Quality of Data

Data and Quality of Data

1. Data and what can be done with data

   • GIGO - Garbage in, Garbage out
   • Data - Raw facts and figures, data can be alphanumeric, graphics, video or sound, data hasn't been processed
   • Information - Data that has been processed by a computer, by having calculations performed on it/put in a meaningful order
     • Data + Meaning + Context = Information
   • Knowledge - The application of information to a situation, by applying rules to information
   • Data - 8, Information - The temperature the meat is kept at, Knowledge - The temperature is above 0 so it will not freeze, just be chilled

2. Data Validation

   • Types of errors
     • Transcription errors - You make an error when typing in data using a document as the source of the data, for example : mishearing somebody on the phone
     • Transposition/input error - You make an error when you are typing and accidently swap the characters round, making them in the wrong order
     • Processing error - Mistakes in formula's/spreadsheets
     • Transmission errors - When data becomes corrupted when it travels through cables/wireless due to electrical interference
   • Data Validation - Performed by the computer when data is entered, validation makes sure the data is sensible, reasonable, complete and within a certain range
   • Validation checks
     • Range check - To make sure a number is within a certain range
     • Presence check - Ensuring that data has been entered into a field
     • Data type check - Making sure that the right type of data in entered, for example : only numbers in a numeric field
     • Format check - Checks to make sure that data includes the right combination of numbers and letters, for example : LLNN LLL for a number plate (L = Letter, N = Number)
     • Check digits - A number at the end of a string of numbers to check that the string of numbers have correctly been inputted into the computer

3. Encoding and storage of data

   • Assigning codes to data to reduce its size
   • For example : size of clothes would be S = Small, M = Medium, L = Large, airport codes would be LHR = London Heathrow, MAN = Manchester
   • Advantages - Takes up less storage, quicker to type into a computer
   • Disadvantages - Easily stolen, training needed for people to learn the codes
   • Good quality data is valid, fit for purpose, up to date and accurate

4. Data Verification

   • Data Verification - Checking that the data that is entered into the ICT system perfectly matches the source of the data, for example : paper form
   • Verification methods
     • Visual check - One user reading carefully what they have typed in and comparing it to the data source, to see if there are any errors that could possible be corrected
     • Double entry of data - Having to enter the same detail twice into the system, with the system only accepting identical details, for example : having to confirm your password
     • Parity check - Checking data after it has been sent through a wire/wireless, to make sure it hasn't been corrupted, for example : when sending an email that you check the text/data in it to make sure when it arrives that no error has been introduced
   • Batch total - A meaningful total, to check that the computer has input all of the data, for example : adding up a batch of sold eBay items
   • Hash total - Meaningless total of numbers , such as order of numbers, used to check that all data has been entered