Question 701 of 982

Describe an analytics workload on Azure →mediumMultiple ChoiceObjective-mapped

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 company needs to ingest data from an on-premises SQL Server database into Azure SQL Database every hour. During the ingestion, they need to filter out rows where Status = 'Inactive' and convert a date column to a different format. They want a cloud-based, code-free solution that can schedule and orchestrate this task. Which Azure service should they use?

Question 1mediummultiple choice

Full question →

A
Azure Logic Apps
Why wrong: Azure Logic Apps is a workflow automation service suitable for integrating applications and data, but it is not optimized for high-volume bulk data transformations and lacks the rich data flow capabilities needed for this ETL task.
B
Azure Data Factory with Mapping Data Flows
Azure Data Factory provides mapping data flows, a visual designer for building data transformations at scale. It integrates with on-premises data via self-hosted integration runtime, supports scheduling, and requires no code, making it the ideal choice.
C
Azure Functions
Why wrong: Azure Functions allows you to write custom code in multiple languages, but it is not a code-free solution. It would require writing code for data extraction, transformation, and loading, which contradicts the requirement for a code-free approach.
D
Azure SQL Database Change Data Capture
Why wrong: Change Data Capture (CDC) tracks row changes in a source database, but it is primarily for incremental data capture, not for scheduled bulk ETL with transformation. It also requires additional components for orchestration.

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 Data Factory with Mapping Data Flows

Azure Data Factory with Mapping Data Flows is the correct choice because it provides a cloud-based, code-free ETL service that can ingest data from on-premises SQL Server into Azure SQL Database, apply transformations like filtering rows (Status = 'Inactive') and converting date formats, and schedule the task using triggers. Mapping Data Flows run on Spark clusters and allow visual data transformation without writing code, making it ideal for this orchestrated, scheduled ingestion.

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 Logic Apps
Why it's wrong here
Azure Logic Apps is a workflow automation service suitable for integrating applications and data, but it is not optimized for high-volume bulk data transformations and lacks the rich data flow capabilities needed for this ETL task.
✓
Azure Data Factory with Mapping Data Flows
Why this is correct
Azure Data Factory provides mapping data flows, a visual designer for building data transformations at scale. It integrates with on-premises data via self-hosted integration runtime, supports scheduling, and requires no code, making it the ideal choice.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Functions
Why it's wrong here
Azure Functions allows you to write custom code in multiple languages, but it is not a code-free solution. It would require writing code for data extraction, transformation, and loading, which contradicts the requirement for a code-free approach.
✗
Azure SQL Database Change Data Capture
Why it's wrong here
Change Data Capture (CDC) tracks row changes in a source database, but it is primarily for incremental data capture, not for scheduled bulk ETL with transformation. It also requires additional components for orchestration.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse Azure Logic Apps with Azure Data Factory because both can schedule and orchestrate tasks, but Logic Apps lacks the native data transformation capabilities (like filtering and date conversion) required for ETL workloads, making Data Factory with Mapping Data Flows the correct choice for code-free data transformation.

Detailed technical explanation

How to think about this question

Under the hood, Azure Data Factory Mapping Data Flows compile into Spark jobs that execute on Azure Databricks clusters, allowing for scalable, in-memory transformations. The on-premises SQL Server connection uses a self-hosted integration runtime (SHIR) that securely communicates over port 443 with Azure, while the date conversion can be performed using built-in derived column transformations with functions like `toDate()` or `toString()`. In a real-world scenario, this setup is often used for hourly data synchronization in retail or finance, where filtering out inactive records and standardizing date formats is critical for downstream analytics.

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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

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

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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 Data Factory with Mapping Data Flows — Azure Data Factory with Mapping Data Flows is the correct choice because it provides a cloud-based, code-free ETL service that can ingest data from on-premises SQL Server into Azure SQL Database, apply transformations like filtering rows (Status = 'Inactive') and converting date formats, and schedule the task using triggers. Mapping Data Flows run on Spark clusters and allow visual data transformation without writing code, making it ideal for this orchestrated, scheduled ingestion.

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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