- A
Transactional data is optimized for write operations, and analytical data is optimized for read operations.
This is correct. OLTP systems are designed for efficient writes, while OLAP systems are designed for complex reads.
- B
Transactional data must always be stored in non-relational databases, and analytical data in relational databases.
Why wrong: This is false. Both transactional and analytical data can be stored in either type of database depending on requirements.
- C
Analytical data always requires real-time processing, whereas transactional data is batch-processed.
Why wrong: This is false. Analytical workloads often use batch processing, and transactional workloads are typically real-time.
- D
Transactional data is read-only and analytical data is frequently updated.
Why wrong: This is false. Transactional data is frequently updated, while analytical data is usually read-only after being loaded.
DP-900 Describe core data concepts Practice Question
This DP-900 practice question tests your understanding of describe core data concepts. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 maintains a database of customer orders that are updated frequently. They also store aggregated monthly sales reports that are generated once and then only read. Which statement correctly distinguishes these two types of data workloads?
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
Transactional data is optimized for write operations, and analytical data is optimized for read operations.
Option A is correct because transactional workloads (like the frequently updated customer orders) are optimized for write-heavy operations, ensuring ACID compliance and data integrity, while analytical workloads (like the read-only monthly sales reports) are optimized for read-heavy operations, often using columnar storage or pre-aggregated data to speed up queries. This distinction aligns with the core difference between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) systems in Azure, such as Azure SQL Database for transactional data and Azure Synapse Analytics for analytical data.
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.
- ✓
Transactional data is optimized for write operations, and analytical data is optimized for read operations.
Why this is correct
This is correct. OLTP systems are designed for efficient writes, while OLAP systems are designed for complex reads.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Transactional data must always be stored in non-relational databases, and analytical data in relational databases.
Why it's wrong here
This is false. Both transactional and analytical data can be stored in either type of database depending on requirements.
- ✗
Analytical data always requires real-time processing, whereas transactional data is batch-processed.
Why it's wrong here
This is false. Analytical workloads often use batch processing, and transactional workloads are typically real-time.
- ✗
Transactional data is read-only and analytical data is frequently updated.
Why it's wrong here
This is false. Transactional data is frequently updated, while analytical data is usually read-only after being loaded.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse the typical characteristics of OLTP and OLAP, mistakenly thinking analytical data requires real-time processing or that transactional data is read-only, when in fact the opposite is true for each.
Detailed technical explanation
How to think about this question
Under the hood, transactional workloads use row-based storage and B-tree indexes to optimize for point lookups and small writes, whereas analytical workloads use columnar storage and compression (e.g., in Azure Synapse’s columnstore indexes) to minimize I/O for large scans and aggregations. A real-world scenario: a retail company’s order database (OLTP) handles thousands of inserts per second with row locks, while the monthly sales report (OLAP) runs a single query scanning millions of rows to compute totals, benefiting from columnar batch processing.
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
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this DP-900 question test?
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: Transactional data is optimized for write operations, and analytical data is optimized for read operations. — Option A is correct because transactional workloads (like the frequently updated customer orders) are optimized for write-heavy operations, ensuring ACID compliance and data integrity, while analytical workloads (like the read-only monthly sales reports) are optimized for read-heavy operations, often using columnar storage or pre-aggregated data to speed up queries. This distinction aligns with the core difference between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) systems in Azure, such as Azure SQL Database for transactional data and Azure Synapse Analytics for analytical data.
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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Last reviewed: Jun 11, 2026
This DP-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-900 exam.
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