Quick Answer
The answer is Power BI, Synapse Data Engineering, and OneLake. These three components form the core of Microsoft Fabric’s end-to-end analytics platform because Fabric unifies data ingestion, transformation, storage, and visualization within a single SaaS experience. Synapse Data Engineering provides Spark-based pipelines for data orchestration, OneLake acts as the single, multi-cloud data lake that eliminates data silos, and Power BI delivers interactive visualization and reporting directly on that lake. On the DP-900 exam, this question tests your understanding of Fabric’s integrated architecture rather than isolated services—a common trap is selecting Azure Synapse Analytics (the older, separate service) instead of Synapse Data Engineering. Remember that Fabric is built around OneLake as its foundation, with Synapse for engineering and Power BI for insight, so think “OneLake + Synapse + Power BI” as the three pillars. A useful memory tip: OSP—OneLake, Synapse, Power BI—covers storage, processing, and presentation in one platform.
This DP-900 practice question tests your understanding of describe an analytics workload on azure. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 THREE components are part of Microsoft Fabric's end-to-end analytics platform? (Choose three.)
Synapse Data Engineering
A workload in Fabric for data transformation.
Azure Machine Learning
Why wrong: Separate service; Fabric has AI capabilities but not ML as a component.
OneLake
The unified data lake in Fabric.
Power BI
Power BI is integrated into Fabric.
Azure DevOps
Why wrong: DevOps is not a Fabric component.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Synapse Data Engineering
Synapse Data Engineering is a core component of Microsoft Fabric, providing a unified platform for data ingestion, transformation, and orchestration using Spark and pipelines. It integrates seamlessly with OneLake for storage and Power BI for visualization, forming part of Fabric's end-to-end analytics solution.
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.
Synapse Data Engineering
Why this is correct
A workload in Fabric for data transformation.
Related concept
Read the scenario before looking for a memorised answer.
Azure Machine Learning
Why it's wrong here
Separate service; Fabric has AI capabilities but not ML as a component.
OneLake
Why this is correct
The unified data lake in Fabric.
Related concept
Read the scenario before looking for a memorised answer.
Power BI
Why this is correct
Power BI is integrated into Fabric.
Related concept
Read the scenario before looking for a memorised answer.
Azure DevOps
Why it's wrong here
DevOps is not a Fabric component.
Common exam traps
The trap here is that candidates may confuse Azure Machine Learning as part of Fabric because both involve AI/analytics, but Fabric's scope is limited to integrated data engineering, lakehouse, and BI components, excluding dedicated ML services.
Detailed technical explanation
Microsoft Fabric unifies data engineering, data integration, data warehousing, and business analytics into a single SaaS experience, with OneLake acting as the single, multi-cloud data lake. Under the hood, OneLake uses Delta-Parquet format for open storage, enabling direct querying by Spark, SQL, and Power BI without data movement. This architecture eliminates the need for separate data silos and reduces latency in real-world analytics pipelines.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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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: Synapse Data Engineering — Synapse Data Engineering is a core component of Microsoft Fabric, providing a unified platform for data ingestion, transformation, and orchestration using Spark and pipelines. It integrates seamlessly with OneLake for storage and Power BI for visualization, forming part of Fabric's end-to-end analytics solution.
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-900 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-900 exam.
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