Question 1easymultiple choice
Full question →easymultiple choiceObjective-mapped
A company is evaluating Azure database services for two different workloads. Workload A processes high-volume, low-latency transactions such as order entry and payment processing, where each transaction updates a few rows. Workload B involves running complex aggregations on terabytes of historical sales data to generate monthly business intelligence reports. Which Azure service is best suited for each workload?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
A. Workload A: Azure SQL Database; Workload B: Azure Cosmos DB
Azure SQL Database is excellent for OLTP, but Workload B is analytics which Cosmos DB is not optimized for; Cosmos DB is a transactional NoSQL database.
B
Best answer
B. Workload A: Azure Cosmos DB; Workload B: Azure Synapse Analytics
Cosmos DB provides low-latency transactions (OLTP) and Synapse Analytics is built for large-scale analytics (OLAP), matching the workloads correctly.
C
Distractor review
C. Workload A: Azure Synapse Analytics; Workload B: Azure SQL Database
Synapse Analytics is not designed for high-volume, low-latency transactions; it is optimized for batch analytics. Azure SQL Database is OLTP, not suited for petabyte-scale aggregations.
D
Distractor review
D. Workload A: Azure Cosmos DB; Workload B: Azure Cosmos DB
While Cosmos DB can handle some analytics with its analytical store, it is not the best choice for complex aggregations on terabytes of data compared to a dedicated data warehouse like Synapse Analytics.
Common exam trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Related practice questions
Related DP-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A data engineer needs to process streaming data from IoT devices and store the results in Azure Data Lake Storage for long-term analytics. The data must be processed in near real-time to detect anomalies and trigger alerts. Which Azure service should the engineer use for stream processing?
Question 2
A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?
Question 3
A data engineer needs to process raw clickstream data from multiple websites that is stored in Azure Blob Storage as JSON files. The processing must run automatically every hour, transform the data into a structured format for reporting, and handle schema changes in the source data without manual intervention. Which Azure service should be used?
Question 4
A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?
Question 5
A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?
Question 6
A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?
FAQ
Questions learners often ask
What does this DP-900 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: B. Workload A: Azure Cosmos DB; Workload B: Azure Synapse Analytics — Workload A is a classic OLTP (Online Transaction Processing) workload requiring fast, individual row operations. Azure Cosmos DB is a globally distributed NoSQL database designed for low-latency reads and writes at scale, making it ideal for high-throughput transaction processing. Workload B is an OLAP (Online Analytical Processing) workload requiring large-scale aggregations. Azure Synapse Analytics is a cloud data warehouse built for massively parallel processing (MPP) to handle complex queries on large datasets. Azure SQL Database is also OLTP-oriented but for relational data; while it could serve Workload A, Cosmos DB is more suitable for scenarios requiring extreme scalability and low latency across multiple regions. However, in this multiple-choice context, the best pair is Cosmos DB for OLTP and Synapse Analytics for OLAP.
What should I do if I get this DP-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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