Capturing and Processing Data

Data, Information and Knowlege

Data – A collection of facts that we store with no context or meaning. Nowadays it is stored on computers. Data is processed to get knowledge. For example ‘green’.

Information – Information is data with meaning. For example ‘the traffic light is green’

Knowledge – Knowledge is when information is applied, for example ‘the traffic light is green so I can go’.

Computers need data because they cannot process information – you have to type something in or click on something for it to understand.

As humans we look around and put together information. We need to do something called data capture to get data that is suitable to put on a computer. For example on reality TV programs such as the X Factor people have to phone in to vote, each person has a different phone numbers.

Humans make mistakes when entering data which could dramatically affect people’s lives.

Paper Forms

Some advantages of paper forms are:
· Force a structure on the data being collected
· Collect the fields of data from everyone they are given to making them easy to process
· Can restrict the answers that people write by giving options – restrict what people write back using tick boxes.

Paper forms also have many disadvantages:
· They can be easily lost
· Handwriting can be hard to read
· They cannot be backed up very easily

Screen Forms

Some advantages of screen forms are:
· You can delete mistakes easily
· Validation – makes sure the information is relevant and makes sure it fits the correct format – e.g. text, numbers, date etc.

Some examples of possible validation rules are:
· No is longer than 15 letters
· Non name surname has numbers in it
· A post code must start with one or two letters
· A date of birth must be between 21 and 65 years ago (e.g. this could be used for job applications)
· A price must be between the lowest and highest possible (e.g. this could prevent entering negative values)

Companies need validation to save them time and money, it makes them more efficient. However validation can not stop all mistakes, it can only make sure that data is of the right type. Humans can still make mistakes in data entry, for example there could be a validation rule that no name has numbers in it, but there could still be a typing error in the name as long as it did not involve a number.