Data Validation

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

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;

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

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).

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.

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

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

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

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

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

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.

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

Boolean Logic AND OR NOT

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

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