In IB Computer Science, students are expected to explain not just how data is stored, but how systems keep data reliable over time. Two key concepts that appear frequently in exams are data integrity and data consistency. These terms are closely related, but they are not identical — and confusing them often costs marks.
IB examiners look for explanations that show cause-and-effect understanding, not just definitions.
What Is Data Integrity?
Data integrity refers to the accuracy, reliability, and correctness of data over its entire lifecycle.
Data has integrity when:
- It is accurate
- It has not been corrupted
- It has not been altered incorrectly
- It remains valid as changes occur
In IB terms, data integrity answers the question:
“Can this data be trusted?”
Why Data Integrity Matters
Poor data integrity leads to:
- Incorrect decisions
- System errors
- Loss of trust
- Serious real-world consequences
For example:
- Incorrect grades in a school system
- Wrong balances in a banking system
- Invalid records in a medical database
This is why systems invest heavily in protecting integrity.
How Data Integrity Is Maintained
Data integrity is maintained through multiple mechanisms, including:
- Validation – preventing invalid data entry
- Verification – ensuring data is entered correctly
- Primary keys – preventing duplicate records
- Foreign keys – ensuring valid relationships
- Access control – preventing unauthorised changes
IB students should understand that integrity is not one feature — it is the result of multiple safeguards working together.
What Is Data Consistency?
Data consistency means that:
- The same data has the same value everywhere it appears
- Related data does not contradict itself
For example:
- A student’s name is identical in all related tables
- An address update is reflected everywhere it is stored
Consistency answers the question:
“Does the data agree with itself?”
Data Consistency in Databases
In well-designed databases:
- Data is stored once
- Other tables reference it using keys
This structure ensures:
- Updates occur in one place
- Inconsistencies are avoided
Normalisation plays a major role in maintaining consistency by:
- Reducing duplication
- Centralising data storage
Integrity vs Consistency: The Key Difference
A strong IB exam distinction is:
- Data integrity: data is correct and trustworthy
- Data consistency: data matches across the system
Data can be:
- Consistent but wrong
- Correct in one place but inconsistent elsewhere
High-quality systems must ensure both.
How Transactions Support Integrity and Consistency
Database transactions help maintain both concepts by ensuring:
- Changes are completed fully
- Partial updates do not occur
- Errors do not leave data in an invalid state
IB students should recognise transactions as a tool for protecting reliability.
Common Student Mistakes
Students often:
- Use integrity and consistency interchangeably
- Define them without examples
- Ignore database design
- Forget the role of keys and access control
Clear distinctions score higher marks.
How This Appears in IB Exams
IB questions may ask students to:
- Define data integrity or consistency
- Explain how systems maintain them
- Identify risks to data reliability
- Apply concepts to real-world scenarios
Explanations with examples earn the most marks.
Final Thoughts
Data integrity ensures that data is accurate and trustworthy, while data consistency ensures that data does not contradict itself across a system. Together, they form the foundation of reliable information systems.
Understanding how integrity and consistency are maintained allows IB Computer Science students to explain why databases are trusted in schools, banks, and online platforms — exactly what examiners expect.
