Data, Information & Knowledge 1

1. Data, Information & Knowledge 1

2. 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?

3. 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

4. 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

5. 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

6. 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

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

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

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

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

11. 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

12. Knowledge Examples • Using the 3 previous examples: • A Marketing Manager could use this information to decide whether or not to raise or lower price y • 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!!!

13. 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…

14. 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

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

16. Revision Tasks • Use the Teach-ICT mini site to make your own notes on the differences between data, knowledge and information http://www.teach-ict.com/as_a2_ict_new/ocr/AS_G061/311_data_info_knowledge/data_info_knowledge/home_data_info_know.html

17. 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.