- A
Keep the single table but use compression to reduce storage
Why wrong: Compression reduces storage size but does not eliminate data redundancy; duplicate values still exist and can cause update anomalies.
- B
Create a view that mirrors the single table but physically store data in separate normalized tables
Why wrong: This describes using a view to simplify queries, but the core design change is normalization. The answer implies the normalization step but does not name it directly.
- C
Normalize the schema by creating separate Students, Courses, and Enrollments tables with foreign keys
Normalization partitions data into entities (Students, Courses) and the relationship (Enrollments). This removes duplication of StudentName and CourseName and enforces referential integrity.
- D
Denormalize by adding more columns to the single table
Why wrong: Denormalization increases redundancy by adding columns, which is the opposite of what is needed to reduce redundancy.
Quick Answer
The correct answer is to normalize the schema by creating separate Students, Courses, and Enrollments tables with foreign keys. This approach directly addresses data redundancy by ensuring each student’s name and each course’s name is stored only once, while foreign keys preserve the relationships needed to reconstruct full enrollment records through JOIN operations. On the Microsoft Azure Data Fundamentals DP-900 exam, this scenario tests your understanding of normalization as a core relational database design principle—specifically, how it eliminates update anomalies and storage overhead. A common trap is assuming that adding more columns or indexes solves redundancy, but the correct solution is always to decompose tables into well-defined entities. For a quick memory tip, remember the mnemonic “One Fact, One Place” to reinforce that normalization means each piece of data lives in exactly one table, linked by keys.
DP-900 Practice Question: Identify considerations for relational data on Azure
This DP-900 practice question tests your understanding of identify considerations for relational data on azure. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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 university's enrollment system stores data in a single table with columns: EnrollmentID, StudentID, StudentName, CourseID, CourseName, and Grade. Students can take multiple courses, and each course has multiple students. The team notices data redundancy: StudentName is repeated for each enrollment of the same student, and CourseName is repeated for each enrollment in the same course. They want to reduce redundancy while preserving the ability to query all enrollments with student and course details. What is the most appropriate design approach?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Normalize the schema by creating separate Students, Courses, and Enrollments tables with foreign keys
Option C is correct because normalizing the schema into separate Students, Courses, and Enrollments tables eliminates data redundancy by storing each student's name and each course's name only once, while using foreign keys to maintain relationships. This preserves the ability to query all enrollments with student and course details via JOIN operations, which is the standard relational database design principle for reducing anomalies and storage overhead.
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.
- ✗
Keep the single table but use compression to reduce storage
Why it's wrong here
Compression reduces storage size but does not eliminate data redundancy; duplicate values still exist and can cause update anomalies.
- ✗
Create a view that mirrors the single table but physically store data in separate normalized tables
Why it's wrong here
This describes using a view to simplify queries, but the core design change is normalization. The answer implies the normalization step but does not name it directly.
- ✓
Normalize the schema by creating separate Students, Courses, and Enrollments tables with foreign keys
Why this is correct
Normalization partitions data into entities (Students, Courses) and the relationship (Enrollments). This removes duplication of StudentName and CourseName and enforces referential integrity.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Denormalize by adding more columns to the single table
Why it's wrong here
Denormalization increases redundancy by adding columns, which is the opposite of what is needed to reduce redundancy.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse views with physical schema changes, thinking a view can magically eliminate redundancy without altering table structure, or they mistakenly believe compression is a substitute for proper normalization.
Detailed technical explanation
How to think about this question
Normalization to Third Normal Form (3NF) ensures that non-key attributes (StudentName, CourseName) depend only on their respective candidate keys (StudentID, CourseID), not on the composite key of the enrollment. In Azure SQL Database, this design supports efficient indexing and reduces I/O during updates, as changing a student's name requires updating only one row in the Students table rather than every enrollment row.
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
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Questions learners often ask
What does this DP-900 question test?
Identify considerations for relational data on Azure — This question tests Identify considerations for relational data on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Normalize the schema by creating separate Students, Courses, and Enrollments tables with foreign keys — Option C is correct because normalizing the schema into separate Students, Courses, and Enrollments tables eliminates data redundancy by storing each student's name and each course's name only once, while using foreign keys to maintain relationships. This preserves the ability to query all enrollments with student and course details via JOIN operations, which is the standard relational database design principle for reducing anomalies and storage overhead.
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.
About these practice questions
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Same concept, more angles
2 more ways this is tested on DP-900
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A database designer is creating a relational database for a library system. Each book can have multiple authors, and each author may have written many books. To avoid data redundancy, the designer creates a separate Authors table and a BookAuthors junction table. This process of organizing data to reduce redundancy and improve integrity is called:
medium- A.Denormalization
- B.Indexing
- ✓ C.Normalization
- D.Partitioning
Why C: Normalization is the process of organizing data in a relational database to reduce redundancy and improve data integrity by dividing large tables into smaller, related tables and defining relationships between them. In this scenario, creating separate Authors and BookAuthors junction tables eliminates the redundancy of storing author information multiple times for each book, which is a classic example of normalization (specifically achieving third normal form). This directly supports the relational database goal of minimizing duplicate data and ensuring consistency.
Variation 2. A database designer wants to reduce data redundancy and improve data integrity by splitting a large table into multiple related tables based on functional dependencies. This process is known as:
medium- A.Denormalization
- ✓ B.Normalization
- C.Partitioning
- D.Indexing
Why B: Normalization is the process of organizing a relational database into multiple related tables to reduce data redundancy and improve data integrity by eliminating functional dependencies that cause anomalies. This is a core concept in relational database design, directly aligning with the scenario described in the question.
Last reviewed: Jun 11, 2026
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