Checking the accuracy of data

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Checking the Accuracy of Data

Information Technology 9626 - Section 1.4

Validation and Verification Methods for Data Integrity

Interactive Revision Notes with Self-Testing

Validation vs. Verification: The Difference
Data Validation Methods
Presence Check & Range Check
Type Check & Length Check
Format Check & Check Digit
Lookup Check & Consistency Check
Limit Check
Data Verification Methods
Why Both Are Needed
Summary and Review

1. Validation vs. Verification: The Core Difference

Learning Objectives:

Understand the difference between validation and verification
Know what each method checks
Recognize why both are essential

The Problem: Data Entry Errors

Data entry is one of the most time-consuming and error-prone parts of data processing. When users enter data, mistakes happen. Without checks, these errors propagate through the system and produce inaccurate results.

⚠ Classic Example: A utility company sent a customer a bill for $1,000,000 instead of $10! This was the result of poor checking. The decimal point was misplaced, but nobody caught it.

Two Methods to Prevent Errors

Aspect	Validation	Verification
What it checks	Data is REASONABLE and SENSIBLE	Data has been COPIED or ENTERED ACCURATELY
Who performs it	Computer only (automatic)	Computer OR human
Does it check correctness?	NO—only that it's reasonable	Only that it matches the source document
Example	Cost between $10-$29 (reasonable range)	Check data matches source (spelling, typos)
Limitation	Won't catch unreasonable data that's typed correctly	Won't catch if ORIGINAL data was wrong

✓ Critical Principle: Neither validation nor verification ensures data is CORRECT. They only ensure:

Validation: Data looks reasonable (could still be wrong)
Verification: Data was transferred accurately (original data might be wrong)

Quick Question 1

What is the key difference between validation and verification?

2. Data Validation Methods Overview

In This Section:

Learn 9 different validation methods
Understand when each method is used
See how they work with database examples

The 9 Validation Methods

✓ Important Note: Not every field can have validation. For example, personal names have so many variations (apostrophes, accents, different languages) that validation would be very difficult. Validation is designed for fields with predictable patterns.

The following validation methods are used depending on the field type and data:

Method	What It Checks	Best Used For
Presence Check	Data has been entered in field	Key fields (ID, ISBN)
Range Check	Data is within min-max values	Numeric fields (cost, age, date)
Type Check

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Also in the full note

3. Presence Check & Range Check
4. Type Check & Length Check
5. Format Check & Check Digit
6. Lookup Check & Consistency Check
7. Limit Check
8. Data Verification Methods
9. Why Both Validation and Verification Are Needed
10. Summary and Review

What's inside

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Checking the accuracy of data