A/S ICT IT1 4.1.1 Data, information and knowledge The relationship between data, information and knowledge. Candidates should understand that: data consists of raw facts and figures e.g. readings from sensors information is data which has been processed by a computer system knowledge is derived from information by applying rules to it from the Specification

4.1.1 The relationship between data, information and knowledge Raw facts and figures before processing. On their own they have no meaning. e.g. readings from sensors, test results, survey facts Information Data which has been processed (organised, sorted, formatted, calculated ) by a computer system. It has been put into a context which makes it meaningful Knowledge Is derived from information by applying rules to it in order to understand or interpret it. Knowledge is used in making decisions.

Data, Information, Knowledge Example 1 Data: 1,12, 1.4,2, 12, 1.2, 3,16, 1.1 Information: Swim times for 100m Swimmer No Age group Times (mins) 1 12 1.4 2 1.2 3 16 1.1 Knowledge: Swimmer No 2 is the fastest in the age 12 group. Data is processed to become information. Rules are applied to information, and it becomes knowledge

4.1.1 Data, Information, Knowledge Example 2 This set of numbers are data representing a set of test results for a student. (On their own they have no meaning because they have no context.) Information: The data has been processed and given context. It is now meaningful information. Jon Ward’s results Test 1 Test 2 Test 3 Raw mark 20 25 30 Max mark 50 100 Percentage 100% 50% 30% Knowledge The teacher can see that Jon’s results are showing a downward trend. The teacher applies the rule of 40% for a pass to gain the knowledge that Jon has passed Tests 1 and 2, and failed Test 3.

4.1.1 Data, Information, Knowledge Example 3 A list of numbers representing item codes and quantities sold this month. Information The data are grouped by branch, amounts paid are calculated and totalled. The processed information is added to a Monthly Branch Sales Report (context) and formatted (currency format) for the Manager. Monthly Branch Sales Report 01/01/08 Leicester £30 000.00 Nuneaton £10 000.00 Coventry £20 000.00 Knowledge The manager applies the rules about performance targets to gain knowledge of which branches meet the requirements for a bonus payment this month.

4.1.1 DATA, INFORMATION AND KNOWLEDGE Task 1 Raw data   Sunil’s test results were: Test 1: 25 marks, Test 2: 25 marks Jon’s test result Test 1: 20 marks, Test 2: 30 marks  Information After processing the test results in order to convert the data into useful information, the teacher decided that Sunil’s results were better than Jon’s. Question 1. Can you explain how that could happen?

Task 1 Question 2 Knowledge After further processing with additional data, the teacher decided that neither boy deserved an end of year prize for doing well. Question 2. Can you explain why she might make that decision?

4.1.1 Data, information and knowledge The reasons for encoding data and the problems associated with encoding. Candidates should understand why data is encoded and the potential problems associated with this, especially value judgements. from the Specification

4.1.1 Encoded Data Advantages Speeds up data entry because the codes are short and the user may click to select the code from a list. Reduces the chance of errors in data entry as there is less to type in. Codes are shorter than original data, so saves disc storage space. Disadvantages Coarsens data by fitting it into small number of groups (categories) Value judgments needed to fit data into a certain group (category), so selection of category by data entry staff may not be consistent.

4.1.1 Encoding Example Attendance at work Department heads assess the attendance of each employee over 345 days in the year. The data entry form allows only a choice of 4 categories: Excellent, Very Good, Good, Unsatisfactory. Different managers may put employees with the same attendance into different categories because they are making value judgements. Employees with very different attendance figures may be put into the same category because there are not enough categories to allow precision. ‘Unsatisfactory’ could mean I day less than ‘good’ or 200 days less, because the category might cover a wide range of attendance.

4.1.1 Encoded Data Task 2: Toy animal heights are measured in cm. and height data is encoded using 5 categories: Very tall Tall Average Short Very Short Question: The penguin is 30cm. tall. The elephant is 60 cm. tall. Question 1. Into which categories would you put these two animals? Question 2. What problems / disadvantages may arise from encoding in this case? Exit