- A
Azure SQL Database
Why wrong: Incorrect. Azure SQL Database is optimized for OLTP workloads and lacks the distributed computing and columnar storage support needed for petabyte-scale analytics.
- B
Azure Synapse Analytics
Correct. Synapse Analytics combines SQL query capabilities with MPP architecture and supports columnar storage formats like Parquet, making it ideal for large-scale analytics.
- C
Azure Cosmos DB
Why wrong: Incorrect. Cosmos DB is a globally distributed NoSQL database for real-time transactional applications, not suited for complex analytics on petabyte-scale historical data.
- D
Azure Table Storage
Why wrong: Incorrect. Azure Table Storage is a simple key-value store designed for structured NoSQL data at scale but lacks advanced querying and columnar storage for analytics.
DP-900 Describe an analytics workload on Azure Practice Question
This DP-900 practice question tests your understanding of describe an analytics workload on azure. 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 financial institution needs to run complex queries against petabytes of historical trading data stored in Azure Data Lake Storage. The queries must be efficient and use columnar storage format. Which technology should they use to process this data?
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
Azure Synapse Analytics
Azure Synapse Analytics (formerly SQL Data Warehouse) is the correct choice because it is a cloud-based analytics service designed for petabyte-scale data warehousing. It supports PolyBase to query data directly from Azure Data Lake Storage and uses a columnar storage format (via clustered columnstore indexes) to enable efficient, high-performance analytical queries on massive historical datasets.
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.
- ✗
Azure SQL Database
Why it's wrong here
Incorrect. Azure SQL Database is optimized for OLTP workloads and lacks the distributed computing and columnar storage support needed for petabyte-scale analytics.
- ✓
Azure Synapse Analytics
Why this is correct
Correct. Synapse Analytics combines SQL query capabilities with MPP architecture and supports columnar storage formats like Parquet, making it ideal for large-scale analytics.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Cosmos DB
Why it's wrong here
Incorrect. Cosmos DB is a globally distributed NoSQL database for real-time transactional applications, not suited for complex analytics on petabyte-scale historical data.
- ✗
Azure Table Storage
Why it's wrong here
Incorrect. Azure Table Storage is a simple key-value store designed for structured NoSQL data at scale but lacks advanced querying and columnar storage for analytics.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure SQL Database (a transactional system) with Azure Synapse Analytics (an analytical system), assuming both can handle petabyte-scale analytics, but only Synapse provides the columnar storage and MPP engine required for efficient historical data queries.
Detailed technical explanation
How to think about this question
Azure Synapse Analytics uses a distributed query processing architecture with Massively Parallel Processing (MPP) and separates compute from storage. Its columnstore indexes compress data by column rather than row, reducing I/O and improving scan performance for aggregation-heavy queries. In real-world scenarios, financial firms use Synapse with PolyBase to run T-SQL queries directly against Parquet or ORC files in Azure Data Lake Storage, avoiding costly data movement.
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.
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FAQ
Questions learners often ask
What does this DP-900 question test?
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Synapse Analytics — Azure Synapse Analytics (formerly SQL Data Warehouse) is the correct choice because it is a cloud-based analytics service designed for petabyte-scale data warehousing. It supports PolyBase to query data directly from Azure Data Lake Storage and uses a columnar storage format (via clustered columnstore indexes) to enable efficient, high-performance analytical queries on massive historical datasets.
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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