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FatMax 2007. Licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License
Data, Information &
Knowledge 1

Data
 Data are raw facts and
figures that on their
own have no meaning
 These can be any
alphanumeric
characters i.e. text,
numbers, symbols
Note the “are” bit above? What does this mean?

Data Examples
 Yes, Yes, No, Yes, No, Yes, No, Yes
 42, 63, 96, 74, 56, 86
 111192, 111234
 None of the above data sets have any
meaning until they are given a CONTEXT
and PROCESSED into a useable form

Data Into Information
 To achieve its aims the organisation will
need to process data into information.
 Data needs to be turned into meaningful
information and presented in its most
useful format
 Data must be processed in a context in
order to give it meaning

Information
 Data that has been processed within a
context to give it meaning
OR
 Data that has been processed into a
form that gives it meaning

Examples
 In the next 3 examples
explain how the data
could be processed to
give it meaning
 What information can
then be derived from
the data?
Suggested answers are given at the end of this presentation

Example 1
Yes, Yes, No, Yes, No, Yes,
No, Yes, No, Yes, YesRaw Data
Context
Responses to the market
research question – “Would
you buy brand x at price y?”
Information ???
Processing

Example 2
Raw Data
Context
Information
42, 63, 96, 74, 56, 86
Jayne’s scores in the six
AS/A2 ICT modules
???
Processing

Example 3
Raw Data
Context
Information
111192, 111234
The previous and current
readings of a customer’s
gas meter
???
Processing

Exam Tip
 You’ll nearly always be asked to give
examples of data processed into
information
 Don’t use:
• Traffic lights
• Dates of birth

Knowledge
 Knowledge is the understanding of rules
needed to interpret information
“…the capability of understanding the
relationship between pieces of
information and what to actually do
with the information”
Debbie Jones – www.teach-ict.com

Knowledge Examples
 Using the 3 previous examples:
• A Marketing Manager could use this information to
decide whether or not to raise or lower price
• Jayne’s teacher could analyse the results to determine
whether it would be worth her re-sitting a module
• Looking at the pattern of the customer’s previous gas
bills may identify that the figure is abnormally low and
they are fiddling the gas meter!!!

Knowledge Workers
 Knowledge workers have specialist
knowledge that makes them “experts”
• Based on formal and informal rules they have
learned through training and experience
 Examples include doctors, managers,
librarians, scientists…

Expert Systems
 Because many rules are based
on probabilities computers can
be programmed with “subject
knowledge” to mimic the role
of experts
 One of the most common uses
of expert systems is in
medicine
• The ONCOLOG system shown
here analyses patient data to
provide a reference for doctors,
and help for the choice,
prescription and follow-up of
chemotherapy

Summary
Information Data Context Meaning= ++
Processing
Data – raw facts and figures
Information – data that has been processed (in a context) to give it meaning

Suggested answers to examples
 Example 1
• We could add up the yes and no responses and calculate
the percentage of customers who would buy product X at
price Y. The information could be presented as a chart to
make it easier to understand.
 Example 2
• Adding Jayne’s scores would give us a mark out of 600 that
could then be converted to an A level grade. Alternatively
we could convert the individual module results into grades.
 Example 3
• By subtracting the second value from the first we can work
out how many units of gas the consumer has used. This
can then be multiplied by the price per unit to determine the
customer’s gas bill.

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Unit 2 lo1 2-3

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