Question 1easymultiple choice
Full question →easymultiple choiceObjective-mapped
A company needs to run complex analytical queries that aggregate terabytes of sales data across multiple years. The queries are used for monthly business reports and are not latency-sensitive. The data is stored in Azure Data Lake Storage Gen2. The company wants a fully managed, petabyte-scale data warehouse solution that supports SQL queries and integrates with Power BI for reporting. Which Azure service should they use?
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 Synapse Analytics
Azure Synapse Analytics provides a cloud-based data warehouse that can scale to petabytes. It uses dedicated SQL pools for high-performance analytical queries and has built-in integration with Power BI, Azure Data Lake Storage, and other Azure services.
B
Distractor review
Azure Analysis Services
Azure Analysis Services is an OLAP engine for creating semantic models that aggregate data from various sources. It is not a data warehouse itself; it requires a data source like Synapse or SQL Database to load data into memory for faster analysis.
C
Distractor review
Azure Data Factory
Azure Data Factory is a data integration and ETL service used to orchestrate data movement and transformation. It does not provide a data warehouse for querying; it is used to load data into a warehouse.
D
Distractor review
Azure HDInsight
Azure HDInsight is a managed big data platform for running open-source frameworks like Hadoop, Spark, and Hive. While Hive can provide SQL-like queries, it is not a fully managed data warehouse optimized for petabyte-scale analytics with Power BI integration out of the box.
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 is a limitless analytics service that combines data warehousing, data integration, and big data analytics. Its dedicated SQL pool (formerly SQL Data Warehouse) is designed for petabyte-scale analytics and natively integrates with Power BI. It can query data in Azure Data Lake Storage Gen2 using external tables or PolyBase. Azure Analysis Services is an OLAP engine but not a primary data warehouse. Azure Data Factory is an ETL service. HDInsight is for big data processing with Hadoop/Spark, not a dedicated SQL data warehouse.
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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