The answer is Azure Data Factory and Azure Synapse Pipelines, as both services are purpose-built for orchestrating and automating data pipelines in Azure. Azure Data Factory is a dedicated cloud-based ETL and data integration service that enables you to create, schedule, and orchestrate data pipelines at scale, while Azure Synapse Pipelines, built on the same engine, provides native pipeline orchestration within the Synapse Analytics workspace for moving and transforming data across diverse sources and sinks. On the Microsoft Azure Data Fundamentals DP-900 exam, this question tests your understanding of core data integration services, often appearing as a multiple-select item where a common trap is confusing Azure Data Lake Storage or Azure Databricks—which store or process data but do not orchestrate pipelines—with the correct services. A reliable memory tip is to associate the word “orchestrate” with the conductor of an orchestra: both Data Factory and Synapse Pipelines are the conductors that direct the flow and timing of data movement, not just the instruments that store or compute it.
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.
Which TWO Azure services can be used to orchestrate and automate data pipelines? (Choose two.)
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 Data Factory (E) is a dedicated cloud-based ETL and data integration service that allows you to create, schedule, and orchestrate data pipelines at scale. Azure Synapse Pipelines (B) is built on the same engine as Azure Data Factory and provides native pipeline orchestration within the Synapse Analytics workspace, enabling you to move and transform data across various sources and sinks. Both services offer visual design tools, code-free transformations, and robust scheduling capabilities for automating data workflows.
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 SQL Database
Why it's wrong here
Azure SQL Database is a relational database, not for pipeline orchestration.
✓
Azure Synapse Pipelines
Why this is correct
Azure Synapse Pipelines provide similar orchestration capabilities as Data Factory within Synapse workspace.
Related concept
Read the scenario before looking for a memorised answer.
✗
Power BI
Why it's wrong here
Power BI is a business intelligence tool for visualization, not for pipeline orchestration.
✗
Azure Databricks
Why it's wrong here
Azure Databricks is an analytics platform for big data processing, not a pipeline orchestration service.
✓
Azure Data Factory
Why this is correct
Azure Data Factory is a cloud-based ETL and data integration service that orchestrates data movement and transformation.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Databricks (which can run data transformation code) with a pipeline orchestration service, but it lacks the native scheduling, dependency management, and visual pipeline designer that Azure Data Factory and Synapse Pipelines provide.
Detailed technical explanation
How to think about this question
Under the hood, both Azure Data Factory and Synapse Pipelines use the same integration runtime to connect to on-premises and cloud data stores, supporting activities like Copy Data, Data Flow, and custom .NET or Python activities. They leverage control flow constructs such as ForEach, If Condition, and Until loops to build complex, conditional pipeline logic. A real-world scenario is a daily ETL job that extracts sales data from an on-premises SQL Server, transforms it using mapping data flows, and loads it into Azure Synapse Analytics for reporting—this entire workflow can be orchestrated with a single pipeline and triggered on a schedule or event.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-900 question in full detail.
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 Pipelines — Azure Data Factory (E) is a dedicated cloud-based ETL and data integration service that allows you to create, schedule, and orchestrate data pipelines at scale. Azure Synapse Pipelines (B) is built on the same engine as Azure Data Factory and provides native pipeline orchestration within the Synapse Analytics workspace, enabling you to move and transform data across various sources and sinks. Both services offer visual design tools, code-free transformations, and robust scheduling capabilities for automating data workflows.
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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Question Discussion
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