DP-900 Describe core data concepts Practice Question
Your organization has a data warehouse in Azure Synapse Analytics. You need to load data from Azure Blob Storage daily, transforming it using a data flow. Which Azure service should you use for the ETL process?
⚠ Common exam trap
It's easy for candidates to confuse Azure Synapse Pipelines (which is just ADF inside Synapse) as a separate service, but the correct Azure service name for the ETL tool is Azure Data Factory, not Synapse Pipelines.
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 (ADF) is the correct choice because it provides native integration with Azure Synapse Analytics and Azure Blob Storage, and it includes a visual data flow designer for transforming data without writing code. ADF's mapping data flows execute at scale on Spark clusters, making it ideal for daily ETL workloads that require both ingestion and transformation.
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 Databricks
Why it's wrong here
Azure Databricks is an Apache Spark-based analytics platform that relies on code-first notebooks in Python, Scala, or R for building transformations, so it doesn't offer the no-code, visual mapping data flow experience needed for a purely codeless ETL solution. While it excels at large-scale data engineering and machine learning, its transformation logic is authored explicitly as code, not by dragging activities onto a design canvas like Azure Data Factory.
- ✓
Azure Data Factory
Why this is correct
Azure Data Factory is the correct choice because its mapping data flows provide a visual, code-free environment for designing ETL transformations by connecting source and sink datasets and arranging transformation activities on a canvas. These data flows execute on a managed Spark cluster, allowing complex joins, aggregations, and derived columns to be built declaratively without writing any code, making it the core ETL service for a data warehouse in Azure.
- ✗
Azure Logic Apps
Why it's wrong here
Azure Logic Apps is a low-code integration service designed for automating workflows and connecting hundreds of systems via prebuilt connectors, but its transformation capabilities are limited to simple data operations such as compositions, parse JSON, and select, not the heavy-duty joins and pivots needed for warehouse-scale ETL. It lacks a mapping data flow engine that can perform in-memory transformations on large datasets, so it is inappropriate for complex, high-volume data integration workloads.
- ✗
Azure Synapse Pipelines
Why it's wrong here
Azure Synapse Pipelines, while offering the same mapping data flows as Azure Data Factory because they share the underlying integration engine, are fundamentally embedded within a Synapse workspace; in this scenario the primary, standalone ETL orchestration service is Azure Data Factory itself. Synapse Pipelines are the Synapse-branded equivalent of ADF pipelines, so referencing them as a distinct answer misses that they are technically built on ADF and the enterprise-level data warehouse would typically use Data Factory as the core service.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based data integration, warehousing, and analytics service that brings together big data and data warehouse capabilities under one platform.
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
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Senior Network & Security Engineer · founder of Courseiva
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.