Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A manufacturing company connects thousands of IoT sensors on an assembly line, each sending telemetry data every second. The data volume is terabyte-scale per day. The company needs to analyze the sensor data in near real-time to detect anomalies (e.g., temperature spikes) and also allow data scientists to run interactive ad-hoc queries on the historical data to find patterns. They prefer using a query language similar to SQL. Which Azure service should they choose?
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
Azure Stream Analytics provides real-time stream processing but is designed to send output to sinks (e.g., event hubs, storage) rather than support interactive ad-hoc queries on historical data.
B
Best answer
Azure Data Explorer
Azure Data Explorer is optimized for high-velocity time-series data, supports near real-time anomaly detection, and enables fast interactive queries on both streaming and historical data using a SQL-like language (KQL).
C
Distractor review
Azure Synapse Analytics dedicated SQL pool
Azure Synapse dedicated SQL pool is designed for large-scale data warehousing with T-SQL, but it is not optimized for high-frequency time-series ingestion and interactive ad-hoc queries on streaming data.
D
Distractor review
Azure Databricks with Structured Streaming
Azure Databricks can handle streaming analytics using Spark Structured Streaming, but for interactive ad-hoc queries on live data, it typically has higher latency and requires more complex setup compared to Azure Data Explorer.
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 Data Explorer — Azure Data Explorer (ADX) is purpose-built for interactive analytics on large volumes of streaming and time-series data. It supports ingestion of high-velocity data, near real-time anomaly detection, and fast ad-hoc queries using Kusto Query Language (KQL), which is SQL-like. Azure Stream Analytics is more for real-time processing and output to sinks, not for interactive ad-hoc queries. Azure Synapse dedicated SQL pool is optimized for large-scale data warehousing but less suited for high-frequency time-series. Azure Databricks is powerful but typically uses Spark SQL and has higher latency for interactive queries on streaming data. Therefore, Azure Data Explorer 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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