1. Data Validation

2. Data Validation and Verification
Validation –the checks a computer carries out when data is input, it checks that the data is sensible.
Verification – Ensures the data is accurate

3. Data Validation
It is important to ensure that only correct data is stored and processed.
It may not be possible to ensure the data is correct, but we can make sure it is sensible.
Unfortunately, data that is sensible could still be flawed.
This process is called data validation; it takes place on input, on process and on output.
Various methods that can be used to validate data these include;

4. List Check
This checks the data to see if it is a possible value in a drop down box.
For examples are validating gender Male, Female

5. Range Check
This checks that numbers lie between two delimiting values or a specified range.
An example is the hours in a 24-hour clock, the lower value would be 00 (meaning midnight), the upper value would be 23 (the hour before midnight).

6. Presence Check Missing key data means a record cannot be processed.
Check data has been entered in the field. The field cannot be left empty.
In a patients record it is important that the patients name is on their details.

7. Ensures that information is of the same type
Data Type Check
Ensures that information is of the same type
Not allowing a DATE to be entered into a NUMBER field for example, an error message should be displayed

8. Check Digits
Check digit(s) are calculated and placed at the end of the number.
Many Key fields use check digits for example;

9. Coding Information
It is sometimes useful to code information in database fields.
E.g. Entering subjects for lessons:
MA – Maths
EN - English
FR – French
DT – Design and Technology

10. Advantages of Coding Data
Quicker to enter.
Less typing required.
Less likely to make spelling mistakes.
Uses less computer memory.

11. Data Verification (Accuracy)
Ensures that the data that has been inputted is the same as the original data
Proof reading – Physically checking the data with the naked eye
Double Entry – Re-enter data to doubly ensure data is correct

12. Data Verification (Accuracy)
Parity Check – Checks to make that data sent is the same as the data received when data is transmitted from one computer to another.

13. Testing
Normal Data – information that is expected by the system and is within tolerances and validation
Extreme – information that is outside of tolerances e.g. entering 100 when the system will only allow between 1 and 100
Erroneous (false) – entering names into a date field

14. Boolean Logic
AND OR
NOT

15. Inaccurate Information Consequences
Garbage in Garbage Out – GIGO
Wrong decision making
Profit Loss
Legal Ramifications (DPA)
Data Crash

16. Exam Paper 6 – Questions 6, 11, 15 Exam Paper 5 – Questions 3,7,12, 14