Data integrity is the correct answer because it is the overarching data concept that governs the enforcement of rules like unique order numbers (entity integrity) and mandatory links to existing customer records (referential integrity) to ensure accuracy and consistency in a database. On the Microsoft Azure Data Fundamentals DP-900 exam, this concept tests your understanding of how relational databases maintain reliable data through constraints—a common trap is confusing data integrity with data quality or data security, but integrity specifically focuses on rule-based correctness. A strong memory tip is to think of “integrity” as “intact rules”: if the rules are broken, the data is no longer intact or trustworthy.
DP-900 Describe core data concepts Practice Question
This DP-900 practice question tests your understanding of describe core data concepts. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company stores customer orders in a relational database. The database enforces rules that every order must have a unique order number and must be linked to an existing customer record. This enforcement of rules to ensure accuracy and consistency is an example of which data concept?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Data integrity
Data integrity refers to the enforcement of rules that ensure the accuracy, consistency, and reliability of data throughout its lifecycle. In this scenario, the relational database enforces entity integrity (unique order numbers) and referential integrity (linking orders to existing customer records), which are core mechanisms for maintaining data correctness.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Data schema
Why it's wrong here
A schema is the logical structure of the database (tables, columns) but does not itself enforce rules.
✓
Data integrity
Why this is correct
Data integrity is maintained through constraints like primary keys and foreign keys, which enforce rules to keep data accurate and consistent.
Related concept
Read the scenario before looking for a memorised answer.
✗
Data redundancy
Why it's wrong here
Redundancy is the duplication of data, which is the opposite of what the constraints aim to prevent.
✗
Data latency
Why it's wrong here
Latency refers to the time delay in data transfer or processing, not data quality enforcement.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'data schema' (the structural definition) with 'data integrity' (the enforcement of rules), mistakenly thinking that simply having a schema guarantees data accuracy and consistency.
Detailed technical explanation
How to think about this question
Under the hood, relational databases enforce data integrity through constraints such as PRIMARY KEY (ensuring uniqueness and non-null values) and FOREIGN KEY (ensuring that a value in one table matches a primary key in another). For example, a FOREIGN KEY constraint on the `CustomerID` column in an `Orders` table will reject any insert or update that references a non-existent customer, preventing orphaned records. This is implemented via internal checks during DML operations (INSERT, UPDATE, DELETE) and can be configured with cascading actions (e.g., ON DELETE CASCADE) to maintain referential integrity automatically.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-900 question in full detail.
Describe core data concepts — This question tests Describe core data concepts — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Data integrity — Data integrity refers to the enforcement of rules that ensure the accuracy, consistency, and reliability of data throughout its lifecycle. In this scenario, the relational database enforces entity integrity (unique order numbers) and referential integrity (linking orders to existing customer records), which are core mechanisms for maintaining data correctness.
What should I do if I get this DP-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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