Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A marketing company ingests streaming data from social media feeds into Azure Event Hubs. They want to perform real-time sentiment analysis on the data and store the results in Azure SQL Database for immediate dashboarding. They also need to aggregate the raw data over longer time windows and store it in Azure Data Lake Storage for historical trend analysis. Which combination of Azure services should they use for the two processing paths?
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
Best answer
Azure Stream Analytics for real-time analysis and Azure Data Factory for batch aggregation
Azure Stream Analytics handles real-time processing and outputs to SQL Database. Azure Data Factory can schedule batch pipelines to read raw data from Event Hubs (or captured data) and aggregate it into Azure Data Lake Storage.
B
Distractor review
Azure Databricks for both real-time analysis and batch aggregation
While Databricks can handle both, it requires more complex setup for real-time streaming and is not as simple to integrate directly with Event Hubs as Stream Analytics. The question implies a desire for minimal effort.
C
Distractor review
Azure Stream Analytics for both real-time analysis and batch aggregation
Stream Analytics is designed for continuous streaming queries, not for scheduled batch processing of historical data. It cannot easily perform nightly batch aggregation on stored data.
D
Distractor review
Azure Data Factory for real-time analysis and Azure Databricks for batch aggregation
Data Factory is not a real-time processing engine; it handles scheduled or event-driven batch operations. Using it for real-time sentiment analysis would not meet the low-latency requirement.
Common exam trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
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?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Azure Stream Analytics for real-time analysis and Azure Data Factory for batch aggregation — For real-time sentiment analysis, Azure Stream Analytics is the natural choice because it processes data in motion and can output to Azure SQL Database. For batch aggregation of historical raw data, Azure Data Factory is well-suited to orchestrate recurring jobs that read from Event Hubs (or from stored raw data) and write aggregated results to Azure Data Lake Storage. This combination covers both real-time and batch requirements efficiently.
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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