Quick Answer
Azure Data Factory is the correct choice because it is Microsoft’s cloud-based data integration service built specifically to orchestrate and automate data pipelines, including daily pipeline orchestration with Azure Data Factory. It handles scheduled triggers for recurring runs and uses a Self-Hosted Integration Runtime to securely connect to on-premises SQL Server, then copies the data directly into Azure Synapse Analytics. On the DP-900 exam, this scenario tests your understanding of which service handles ETL/ELT orchestration versus storage or compute services—common traps are confusing Azure Data Factory with Azure Synapse Pipelines (which are actually built on ADF) or with Azure Databricks for processing. Remember the key distinction: if the question says “orchestrate” or “schedule” a pipeline that moves data between sources, the answer is always Azure Data Factory. A simple memory tip: ADF = “Automated Data Flow” for daily jobs.
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 data engineer needs to build a data pipeline that runs daily to copy sales data from an on-premises SQL Server to Azure Synapse Analytics. Which Azure service should they use to orchestrate the pipeline?
Azure Analysis Services
Why wrong: Provides analytical data models, not pipeline orchestration.
Azure Data Factory
Cloud-based ETL and data integration service for orchestration.
Azure Databricks
Why wrong: Used for analytics and ML, not pipeline orchestration.
Azure HDInsight
Why wrong: Managed Apache Hadoop service, not for orchestration.
Answer choices
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 (ADF) is the correct choice because it is a cloud-based data integration service specifically designed to orchestrate and automate data pipelines. It supports scheduled triggers (e.g., daily runs) and provides native connectors to copy data from on-premises SQL Server (via Self-Hosted Integration Runtime) to Azure Synapse Analytics, making it the ideal tool for this ETL/ELT workload.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Azure Analysis Services
Why it's wrong here
Provides analytical data models, not pipeline orchestration.
Azure Data Factory
Why this is correct
Cloud-based ETL and data integration service for orchestration.
Related concept
Read the scenario before looking for a memorised answer.
Azure Databricks
Why it's wrong here
Used for analytics and ML, not pipeline orchestration.
Azure HDInsight
Why it's wrong here
Managed Apache Hadoop service, not for orchestration.
Common exam traps
The trap here is that candidates may confuse Azure Data Factory with Azure Databricks or HDInsight because both can process data, but they overlook that the question specifically asks for orchestration of a scheduled copy pipeline, which is ADF's primary purpose, not a general-purpose analytics platform.
Detailed technical explanation
Under the hood, Azure Data Factory uses a Self-Hosted Integration Runtime (SHIR) to securely connect to on-premises SQL Server over port 1433 (default SQL Server port) via a lightweight agent installed on-premises. The pipeline can be triggered by a tumbling window schedule, ensuring exactly-once processing for daily runs, and uses Copy Activity to move data in parallel chunks for high throughput. A real-world scenario where this matters is when the on-premises SQL Server has a large sales table (e.g., millions of rows) — ADF can use staged copy with PolyBase or COPY INTO to load data into Synapse efficiently, handling schema mapping and data type conversions automatically.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Describe an analytics workload on Azure — This question tests Describe an analytics workload on Azure — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Data Factory — Azure Data Factory (ADF) is the correct choice because it is a cloud-based data integration service specifically designed to orchestrate and automate data pipelines. It supports scheduled triggers (e.g., daily runs) and provides native connectors to copy data from on-premises SQL Server (via Self-Hosted Integration Runtime) to Azure Synapse Analytics, making it the ideal tool for this ETL/ELT workload.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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