Question 428 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 has a data warehouse in Azure Synapse Analytics dedicated SQL pool. They need to load new sales data every night from a CSV file stored in Azure Data Lake Storage Gen2. The load process must be automated, scheduled, and have error handling for failed loads. Which Azure service should they use to orchestrate this process?

Question 1mediummultiple choice

Full question →

A
Azure Data Factory
Azure Data Factory provides pipeline orchestration with scheduling, triggers, and error handling. It can copy data from ADLS Gen2 to Synapse dedicated SQL pool using the 'Copy Data' activity or stored procedure activities.
B
Azure Stream Analytics
Why wrong: Azure Stream Analytics processes real-time streaming data using SQL-like queries. It is not designed for scheduled batch loading of files from a data lake.
C
Azure Databricks
Why wrong: Azure Databricks is a Spark-based analytics platform that can perform data transformations and writes, but it lacks built-in scheduling and orchestration features that are available in Azure Data Factory.
D
Azure Logic Apps
Why wrong: Azure Logic Apps is best for automating workflows between applications (e.g., email, Office 365). It can integrate with Azure services but is not the ideal tool for complex data warehouse loading pipelines.

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

Azure Data Factory is the correct choice because it is a cloud-based ETL service designed specifically for orchestrating and automating data movement and transformation at scale. It supports scheduled triggers, native connectors to Azure Data Lake Storage Gen2 and Azure Synapse Analytics, and built-in error handling via retry policies and failure activities, making it ideal for nightly CSV file loads.

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 Data Factory
Why this is correct
Azure Data Factory provides pipeline orchestration with scheduling, triggers, and error handling. It can copy data from ADLS Gen2 to Synapse dedicated SQL pool using the 'Copy Data' activity or stored procedure activities.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Stream Analytics
Why it's wrong here
Azure Stream Analytics processes real-time streaming data using SQL-like queries. It is not designed for scheduled batch loading of files from a data lake.
✗
Azure Databricks
Why it's wrong here
Azure Databricks is a Spark-based analytics platform that can perform data transformations and writes, but it lacks built-in scheduling and orchestration features that are available in Azure Data Factory.
✗
Azure Logic Apps
Why it's wrong here
Azure Logic Apps is best for automating workflows between applications (e.g., email, Office 365). It can integrate with Azure services but is not the ideal tool for complex data warehouse loading pipelines.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates may confuse Azure Data Factory with Azure Logic Apps because both can schedule and automate tasks, but Logic Apps lacks native data warehouse connectors and high-throughput data movement capabilities required for enterprise ETL workloads.

Detailed technical explanation

How to think about this question

Azure Data Factory uses Integration Runtime to connect to on-premises or cloud data sources, and its pipeline activities can include Copy Activity for moving CSV files from ADLS Gen2 to Synapse Dedicated SQL Pool via PolyBase or COPY INTO for high-throughput ingestion. The service supports dependency-driven pipelines, where a failure in one activity can trigger a separate error-handling path (e.g., sending an alert or logging to a table), and scheduled triggers use cron expressions for nightly execution. In real-world scenarios, Data Factory can also handle incremental loads using watermark columns or change tracking, which is critical for large-scale data warehouses.

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.

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 — Azure Data Factory is the correct choice because it is a cloud-based ETL service designed specifically for orchestrating and automating data movement and transformation at scale. It supports scheduled triggers, native connectors to Azure Data Lake Storage Gen2 and Azure Synapse Analytics, and built-in error handling via retry policies and failure activities, making it ideal for nightly CSV file loads.

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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