Data and Information Details and Differences
- 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?
- 2. 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
- 3. 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
- 4. 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
- 5. 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
- 6. 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 ??? Processing
- 7. Example 2 Raw Data Context Information 42, 63, 96, 74, 56, 86 Jayne’s scores in the six AS/A2 ICT modules ??? Processing
- 8. Example 3 Raw Data Context Information 111192, 111234 The previous and current readings of a customer’s gas meter ??? Processing
- 9. 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
- 10. 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!!!
- 11. 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…
- 12. 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
- 13. 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.
- 14. Data vs. Information Data • raw facts • no context • just numbers and text Information • data with context • processed data • value-added to data – summarized – organized – analyzed
- 15. Data vs. Information • Data: 51007 • Information: – 5/10/07 The date of your final exam. – $51,007 The average starting salary of an accounting major. – 51007 Zip code of Bronson Iowa.
- 16. Data vs. Information Data • 6.34 • 6.45 • 6.39 • 6.62 • 6.57 • 6.64 • 6.71 • 6.82 • 7.12 • 7.06 SIRIUS SATELLITE RADIO INC. $5.80 $6.00 $6.20 $6.40 $6.60 $6.80 $7.00 $7.20 1 2 3 4 5 6 7 8 9 10 Last 10 Days Stock Price Information
- 19. Data Information Knowledge Data Information Summarizing the data Averaging the data Selecting part of the data Graphing the data Adding context Adding value
- 20. Data Information Knowledge Information Knowledge How is the info tied to outcomes? Are there any patterns in the info? What info is relevant to the problem? How does this info effect the system? What is the best way to use the info? How can we add more value to the info?
- 21. Information Systems Generic Goal: • Transform Data into Information – At the Core of an Information System is a Database (raw data).
- 22. Information Systems (TSP and PCS) • Data doesn’t just appear, Capturing Data is really the first step • These systems help capture data but they also have other purposes (goals): 1. Transaction Processing Systems (TPS) 2. Process Control Systems (PCS)
- 23. Capturing Data • What are some examples of real TPS’s? • What kind of data is being capture? • How is this data transformed into Information?
- 24. Data Processing • Recall that a basic system is composed of 5 components – Input, Output, Processing, Feedback, Control • Typically processing helps transform data into information. Input Output Processing Raw Data Information
- 25. Processing • Summarizing • Computing Averages • Graphing • Creating Charts • Visualizing Data
- 26. Processing: Great Example • Navigation System – Specialized Geographic Information System • Input: Maps, Addresses, Points of Interest, “Yellow Pages” • Processing: – Computing Shortest Paths; – Finding the Nearest Chinese Restaurant • Output: – Directions (each turn + a map with arrows) – List of nearby Chinese Restaurants (sorted by dist.)
- 27. Analysis – Navigation System • Recall that Information Systems have five more specific components: • People, Data, Communication Network, Hardware, Software. • In a Navigation System… – what is the Communication Network? – what is the Hardware? – who are the People?
- 28. Course Goal: Help you analyze systems? • Step 1: Always ask yourself…What is the purpose of the system? • Step 2: Identify People, Data, Hardware, Software, Communication Network. • Step 3: Identify Input, Output, Processing, Feedback, Control.
- 29. Navigation System Feedback • So what is the feedback in a navigation system? • Feedback is information about how the system is performing. – Feedback can help you identify problems with the system…so you can improve it. • Feedback helps you determine if the system is achieving its goal. – In a heating system, the feedback was the actual temperature.
- 30. Navigation System Control • So what are some of the controls in a navigation system? • Control: Changing a variable to help the system reach its goal or to set a new goal. • In a heating system, the control was the desired temperature.
- 31. Navigation System Control • Obviously, entering a new destination • Not so obvious… – zooming in – changing the map view – selecting an alternative route
- 32. Key Points • A Navigation System takes raw data (maps, locations) and displays it visually (data information) so that it is easier to drive to a location. Goal • The feedback (your current location) is perhaps the most important feature. • Paper maps can NOT show your location.
- 33. Geographic Information Systems (GIS • In lab we are going to learn more about… 1. GIS systems… • Data more informational (more valuable) if you visualize it on a map. 2. Attributes that make information more valuable… • Information is more valuable if it helps you achieve your goal.
- 34. Summary Information Data Context Meaning = + + Processing Data – raw facts and figures Information – data that has been processed (in a context) to give it meaning