Question 260 of 982

Describe an analytics workload on Azure →hardMultiple ChoiceObjective-mapped

Quick Answer

Azure Synapse Analytics is the correct choice because it unifies enterprise data warehousing and big data analytics into a single service, directly supporting complex SQL queries that join Parquet files in ADLS Gen2 with reference data from Azure SQL Database. Its built-in row-level security and column-level security enforce granular access control at the row and column level, meeting the enterprise-grade security requirement, while Synapse Pipelines handle ETL transformations to build a curated layer without needing separate tools. On the DP-900 exam, this scenario tests your understanding of Synapse Analytics as the go-to service for combining serverless SQL queries on data lakes with dedicated SQL pools and integrated security—a common trap is choosing Azure Data Factory alone, which lacks native SQL querying and RLS. Remember the memory tip: “Synapse stitches security, SQL, and ETL in one synapse.”

DP-900 Describe an analytics workload on Azure Practice Question

This DP-900 practice question tests your understanding of describe an analytics workload on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A financial services company has raw transaction data stored in Azure Data Lake Storage Gen2 (ADLS Gen2) as Parquet files, partitioned by date. The analytics team needs to run complex SQL queries that join multiple datasets, including reference data from an Azure SQL Database, to generate risk reports. They require enterprise-grade security features such as row-level security (RLS) and column-level security. They also want to use the same service for data transformation and loading (ETL) into a curated layer. Which Azure service should they choose?

Question 1hardmultiple choice

Full question →

A
Azure Synapse Analytics
Correct. Azure Synapse Analytics offers a unified experience for data integration, enterprise data warehousing, and big data analytics, with built-in security features like RLS and column-level security. It can query ADLS Gen2 using serverless SQL pool and orchestrate ETL with pipelines.
B
Azure Data Factory
Why wrong: Azure Data Factory is primarily a data integration and orchestration service. While it can move and transform data, it does not natively support running complex SQL queries with row-level security.
C
Azure Databricks
Why wrong: Azure Databricks is an Apache Spark-based analytics platform. It excels at data engineering and machine learning but does not provide built-in row-level or column-level security for SQL queries. Security is typically managed at the file or workspace level.
D
Azure Analysis Services
Why wrong: Azure Analysis Services is an analytical engine used to create semantic models. It does not directly query ADLS Gen2; data must be loaded from a source. It also does not include ETL capabilities.

Full breakdown with real-world context →

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Azure Synapse Analytics

Azure Synapse Analytics is the correct choice because it provides a unified analytics platform that combines enterprise data warehousing with big data analytics. It directly supports complex SQL queries across multiple datasets (including Parquet files in ADLS Gen2 and Azure SQL Database), offers built-in row-level security (RLS) and column-level security for enterprise-grade access control, and includes a built-in pipeline orchestration engine (via Synapse Pipelines) for ETL/ELT transformations into a curated layer. This single service eliminates the need to stitch together separate tools for querying, security, and data transformation.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
Azure Synapse Analytics
Why this is correct
Correct. Azure Synapse Analytics offers a unified experience for data integration, enterprise data warehousing, and big data analytics, with built-in security features like RLS and column-level security. It can query ADLS Gen2 using serverless SQL pool and orchestrate ETL with pipelines.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Data Factory
Why it's wrong here
Azure Data Factory is primarily a data integration and orchestration service. While it can move and transform data, it does not natively support running complex SQL queries with row-level security.
✗
Azure Databricks
Why it's wrong here
Azure Databricks is an Apache Spark-based analytics platform. It excels at data engineering and machine learning but does not provide built-in row-level or column-level security for SQL queries. Security is typically managed at the file or workspace level.
✗
Azure Analysis Services
Why it's wrong here
Azure Analysis Services is an analytical engine used to create semantic models. It does not directly query ADLS Gen2; data must be loaded from a source. It also does not include ETL capabilities.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Azure Data Factory as a complete analytics solution because of its ETL capabilities, overlooking that it lacks a native SQL query engine and built-in row/column-level security for direct data access.

Detailed technical explanation

How to think about this question

Azure Synapse Analytics uses a distributed SQL engine (formerly SQL Data Warehouse) that leverages PolyBase to query external data in ADLS Gen2 as if it were relational tables, enabling seamless joins with Azure SQL Database via linked servers or external tables. Its column-level security is implemented through GRANT statements on specific columns, while row-level security uses predicate-based functions that filter rows at query execution time, both enforced at the database engine level. The Synapse Pipelines component is built on Azure Data Factory's orchestration engine, allowing you to define data flows that transform raw Parquet data into curated tables within the same Synapse workspace, all governed by a single security model.

KKey Concepts to Remember

Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.

TExam Day Tips

Watch for words such as best, first, most likely and least administrative effort.
Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.

What to study next

Got this wrong? Here's your next step.

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FAQ

Questions learners often ask

What does this DP-900 question test?

Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Azure Synapse Analytics — Azure Synapse Analytics is the correct choice because it provides a unified analytics platform that combines enterprise data warehousing with big data analytics. It directly supports complex SQL queries across multiple datasets (including Parquet files in ADLS Gen2 and Azure SQL Database), offers built-in row-level security (RLS) and column-level security for enterprise-grade access control, and includes a built-in pipeline orchestration engine (via Synapse Pipelines) for ETL/ELT transformations into a curated layer. This single service eliminates the need to stitch together separate tools for querying, security, and data transformation.

What should I do if I get this DP-900 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Same concept, more angles

1 more ways this is tested on DP-900

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A company uses Azure Data Lake Storage Gen2 as a data lake. They need to enforce row-level security for sensitive data so that sales representatives can only see rows for their assigned region. Which approach should they use?

hard

A.Apply sensitivity labels in Microsoft Purview
✓ B.Load data into Azure Synapse Analytics dedicated SQL pool and implement row-level security (RLS)
C.Use Azure RBAC roles on the storage account
D.Use Azure Data Lake Storage Gen2 access control lists (ACLs) on folders per region

Why B: Row-level security (RLS) in Azure Synapse Analytics dedicated SQL pool allows you to restrict data access at the row level based on a user's identity or group membership. By loading the data into a dedicated SQL pool and defining a security policy with a predicate function that filters rows by region, you can ensure sales representatives only see rows for their assigned region. This is the correct approach because RLS is designed specifically for this purpose and integrates with Azure Active Directory for user authentication.

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