Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A financial analytics company stores petabytes of transaction data in Parquet files in Azure Data Lake Storage Gen2. Data analysts need to run complex SQL queries that join multiple large tables and return results within seconds. The company also wants to integrate with Power BI for visualization and Azure Data Factory for ETL orchestration. They require a massively parallel processing (MPP) engine to handle the scale. 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
Best answer
Azure Synapse Analytics dedicated SQL pool
Correct. The dedicated SQL pool in Azure Synapse Analytics is an MPP engine optimized for large-scale analytical workloads. It can query data directly in ADLS Gen2 via PolyBase, supports complex joins, and integrates with Power BI and Azure Data Factory.
B
Distractor review
Azure SQL Database
Incorrect. Azure SQL Database is an OLTP relational database not designed for petabyte-scale analytics with MPP. It has scalability limits and is not optimized for complex, high-concurrency analytical queries.
C
Distractor review
Azure Cosmos DB
Incorrect. Azure Cosmos DB is a NoSQL database for globally distributed transactional workloads. While it supports SQL-like queries, it is not an MPP data warehouse and cannot efficiently execute complex joins over petabytes of data.
D
Distractor review
Azure Analysis Services
Incorrect. Azure Analysis Services is a semantic modeling engine used to create tabular models for business intelligence. It is not a data warehouse and does not natively store or query petabytes of raw data; it imports data from other sources.
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 dedicated SQL pool — Azure Synapse Analytics is a cloud-based analytics service that provides a massively parallel processing (MPP) engine for large-scale data warehousing. Its dedicated SQL pool (formerly Azure SQL Data Warehouse) can run complex queries across petabytes of data with fast performance. It integrates natively with Power BI and Azure Data Factory. Azure SQL Database and Azure Cosmos DB are not MPP engines designed for petabyte-scale analytics, while Azure Analysis Services is a semantic model not a 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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