Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A manufacturing company ingests real-time sensor data from factory equipment via Azure Event Hubs. The data is a continuous stream of measurements (sensorId, timestamp, value). Additionally, historical maintenance records are stored as CSV files in Azure Data Lake Storage Gen2. The operations team needs to join the streaming data with the historical records in near real-time to detect anomalies. They also need to run complex T-SQL queries on the combined dataset for ad-hoc analysis. Which Azure service should they use as the primary analytics platform?
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
Azure Stream Analytics
Stream Analytics excels at real-time processing but does not support ad-hoc T-SQL queries or joining with historical data in a data lake directly.
B
Best answer
Azure Synapse Analytics
Synapse Analytics unifies big data and data warehousing, enabling T-SQL queries on both streaming and batch data from Event Hubs and Data Lake Storage.
C
Distractor review
Azure Data Factory
Data Factory is an ETL and data integration service, not a query engine for ad-hoc analytics.
D
Distractor review
Azure HDInsight with Spark
HDInsight with Spark can process streaming and batch data, but uses Spark SQL (not T-SQL) and requires more operational overhead.
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 Synapse Analytics — Azure Synapse Analytics (formerly SQL Data Warehouse) provides a unified analytics platform that can ingest streaming data (via Synapse Link or pipelines from Event Hubs) and query it alongside data in Azure Data Lake Storage Gen2 using T-SQL. It supports near real-time processing and ad-hoc analysis with a massively parallel processing (MPP) engine. Azure Stream Analytics is real-time processing but limited to streaming operations and does not natively support complex T-SQL queries on combined batch and streaming data. Azure Data Factory is an orchestration tool, not an analytics engine. Azure HDInsight with Spark uses Spark SQL, not T-SQL, and requires more management. Thus, Synapse Analytics is the best fit.
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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