Unit 2. Data, Knowledge, Information.pptx

Data, Knowledge, and Information.pptx

1. Data, Information & Knowledge

2. The old adage / saying goes along the lines that knowledge can be defined as knowing a tomato is a fruit … And that wisdom is therefore knowing that you don't add a tomato to a fruit salad ... There are a number of models and frameworks that investigate the data-information-knowledge- wisdom continuum h’mm – ict

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5. 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? h’mm – ict

6. Data Examples h’mm – ict  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

7. Data Into Information h’mm – ict  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

8. Information h’mm – ict  D at a t h a t h a s b e e n p ro c e s s e d with i n a context to give it meaning OR  Data that has been processed into a form that gives it meaning

9. 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 h’mm – ict

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

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

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

13. Encoding Information h’mm – ict • Processing turns data into information • Sometimes you might want to turn information into data – i.e. to store it – this is called encoding • How do you code information to make it easy to re-process, without losing it’s meaning?

14. Sources of Data h’mm – ict Internal or External? • Internal communication is communication with people inside the same organisation or company • External communication is with people outside the company, such as suppliers or customers. Direct or Indirect? • Direct data are collected for the purpose of the processing being undertaken – e.g. time cards for pay • Indirect data are originally collected for another purpose, but is now being processed to provide extra information - e.g. spending patterns from credit cards

15. Information Channels h’mm – ict Formal or Informal? • Formal channels are the official (or reliable!) ones, such as memos, letters, the company noticeboard, etc. • Informal channels are the unofficial ones, such as office gossip, informal meetings and rumours – these can often be unreliable.

16. The Value of Information h’mm – ict • It is often said that we are in the information age , and that information is a valuable commodity. • Why is information valuable? Because: • It allows us to plan how to run our business more effectively – e.g. shops can stock what customers want, when they want it, and manufacturers can anticipate demand • Marketing materials can be targeted at people and customers that you know could be interested in your products and services • This can lead to increased customer satisfaction and therefore profit

17. Good Quality Information • The characteristics of good quality information – it should be: • Accurate • Up-to-date • Relevant • Complete • On-time • Appropriately presented

18. Collecting Information h’mm – ict How is information about people collected? 1. Obviously you can ask people questions about their spending habits, etc. (but they might not like it!) 2. Or you can use a more indirect approach: • • • Supermarket loyalty cards - e.g. easily identify vegetarians! Credit card transactions - amounts and locations - can help prevent fraud, too! ATMs, CCTV, till transactions, etc.

19. Coding Information h’mm – ict • • • Information stored in a computer is often coded Coding categorises information and can replace long, description strings with a few letters or numbers (or both!) You are probably familiar with examples such as F for female and M for male

20. Coding - Advantages h’mm – ict Information is often coded because: • • • • • It is quicker to enter into the computer It require less disc space to store, and less memory to process It can make processing easier – or possible – as there will be fewer responses It improves the consistency of the data as spelling mistakes are less likely Validation is easier to apply

21. Coding - Disadvantages h’mm – ict Coding also has some negative effects : • • Information is coarsened by forcing it all into categories – there might not be a category that matches what you want to record – e.g. hair colour The same can be true of rounding numbers – the intervals ( An Interval is all the numbers between two given numbers. Showing if the beginning and end number are included is important. There are three main ways to show intervals :) or numbers of categories , this needs to be chosen carefully to maintain the quality of the information

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

23. Knowledge h’mm – ict  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”

24. K n o wl e dge h’mm – ict • • • • • Data and information deal with facts and figures Knowing what to do with them requires knowledge Knowledge = information + rules Rules tell us the likely effect of something For example: you are more likely to pass your A level IF you do your coursework and revise for your exam!

25. Knowledge Examples h’mm – ict  Using the 3 previous examples: • A Marketing Manager could use this information to decide whether or not to raise or lower price y • 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!!!

26. Knowledge Workers h’mm – ict  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…

27. 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 h’mm – ict

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