Data Handling

Description

Mind Map on Data Handling, created by wmatthew on 20/04/2014.
wmatthew
Mind Map by wmatthew, updated more than 1 year ago
wmatthew
Created by wmatthew over 10 years ago
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Resource summary

Data Handling
  1. Data Validation: Checks that data entered is reasonable but cannot check it is correct.
    1. Range check: It checks the length of the data entered is within a certain range.
      1. Presence check: Makes sure data has been entered in a cell.
        1. Format check: Makes sure data has been entered in the correct format e.g. date of birth.
          1. Length check: It checks the data isn't to short or long.
            1. Check Digit: It puts digits into a calculation to check they are valid commonly used on barcodes.
              1. Lookup Check: It checks the data is correct from a table stored else where.
              2. Data Types
                1. Text: stores both letters and numbers.
                  1. Integer: Stores whole numbers that don't begin with zero.
                    1. Real Number: Stores only decimal numbers however they cant start with zero.
                      1. Date: Is used to store date in the correct format however their is a format choice. Short date e.g. 03/09/2020 or long date e.g. 3rd September 2020
                        1. Boolean: offers a choice of one or the other. Yes/no.
                          1. List: Offers a few select items on a list reducing mistake.
                          2. Databases
                            1. Relational database
                              1. It links several tables together saving on data duplication saving on mistakes but also time
                                1. Can be used to enforce rules by brining up error messages when certain rules are broken.
                                  1. Easy to run a query.
                                  2. Flat file database
                                    1. One large database holding all the information means some data may be keyed twice
                                      1. Difficult to read and use day to day
                                        1. Difficult to run a query on a large table.
                                          1. More prone to mistakes due to confusing layout.
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