1. 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

2. 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.

3. 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. 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.

5. 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 /01/08
Leicester £
Nuneaton £
Coventry £
Knowledge
The manager applies the rules about performance targets to gain knowledge of which branches meet the requirements for a bonus payment this month.

6. 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?

7. 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?

8. 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

9. 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.

10. 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.

11. 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