Quick Answer
The answer is Azure Data Factory and Azure Synapse Pipelines. Both services allow you to orchestrate data pipelines with transformation in Azure by leveraging a shared integration runtime to execute activities like Data Flows, Stored Procedures, or custom code, enabling you to build, schedule, and monitor complex ETL workflows without managing underlying infrastructure. On the DP-203 exam, this concept tests your understanding of native orchestration tools within the Azure ecosystem, often appearing in scenario-based questions where you must choose between these two and distractors like Azure Databricks or Logic Apps. A common trap is assuming only Data Factory handles transformation, but Synapse Pipelines offer identical orchestration capabilities with deeper integration into the Synapse workspace. Remember the mnemonic “ADF and Synapse, the pipeline pair” to recall that both services share the same orchestration engine for transformation-heavy workloads.
This DP-203 practice question tests your understanding of design and implement data storage. 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.
Which TWO of the following Azure services can be used to orchestrate data pipelines that include data transformation?
Azure Synapse Pipelines
Synapse Pipelines are built on ADF and provide similar capabilities.
Azure Data Factory
ADF provides data orchestration and transformation.
Azure Logic Apps
Why wrong: Logic Apps is for business process workflows.
Azure Databricks
Why wrong: Databricks is a compute platform, not an orchestrator.
Azure Functions
Why wrong: Functions is a compute service for event-driven code.
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 Synapse Pipelines
Azure Synapse Pipelines (option A) is correct because it provides a native orchestration service within Azure Synapse Analytics for building, scheduling, and monitoring data pipelines that include data transformation activities, such as Data Flow or Stored Procedure tasks. It leverages the same integration runtime as Azure Data Factory and supports both code-free and code-based transformation steps.
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 Synapse Pipelines
Why this is correct
Synapse Pipelines are built on ADF and provide similar capabilities.
Related concept
Read the scenario before looking for a memorised answer.
Azure Data Factory
Why this is correct
ADF provides data orchestration and transformation.
Related concept
Read the scenario before looking for a memorised answer.
Azure Logic Apps
Why it's wrong here
Logic Apps is for business process workflows.
Azure Databricks
Why it's wrong here
Databricks is a compute platform, not an orchestrator.
Azure Functions
Why it's wrong here
Functions is a compute service for event-driven code.
Common exam traps
The trap here is that candidates often confuse compute services (like Databricks or Functions) with orchestration services, mistakenly thinking they can replace Azure Data Factory or Synapse Pipelines for end-to-end pipeline management, when in fact they are typically used as activities within an orchestrated pipeline.
Detailed technical explanation
Under the hood, both Azure Synapse Pipelines and Azure Data Factory use the same Integration Runtime (IR) to connect to data sources and execute activities, including Mapping Data Flows that run on Spark clusters for transformation. A subtle behavior is that Synapse Pipelines can directly reference Synapse SQL pools or Spark pools as compute targets, while Data Factory requires linked services to connect to external compute like Databricks or HDInsight. In a real-world scenario, you might use Synapse Pipelines to orchestrate a pipeline that ingests raw data from Blob Storage, transforms it using a Data Flow, and loads it into a dedicated SQL pool—all within a single managed environment.
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
Design and implement data storage — This question tests Design and implement data storage — Read the scenario before looking for a memorised answer..
The correct answer is: Azure Synapse Pipelines — Azure Synapse Pipelines (option A) is correct because it provides a native orchestration service within Azure Synapse Analytics for building, scheduling, and monitoring data pipelines that include data transformation activities, such as Data Flow or Stored Procedure tasks. It leverages the same integration runtime as Azure Data Factory and supports both code-free and code-based transformation steps.
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
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.
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