The correct answer is Azure Data Lake Storage Gen2. This component is primarily used to store raw data in its native format within a lakehouse architecture because it provides a scalable, hierarchical file system that accepts any file type—such as CSV, JSON, or Parquet—without requiring a predefined schema, perfectly supporting the "schema-on-read" approach. On the Microsoft Azure Data Fundamentals DP-900 exam, this question tests your understanding of how Azure Synapse Analytics separates storage from compute, with ADLS Gen2 serving as the raw data landing zone before processing. A common trap is confusing Azure Synapse SQL pools or pipelines with storage; remember that raw data lives in the lake, not in a database table. For a memory tip, think "ADLS Gen2 = the raw data bucket" where you dump files first, then transform later.
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.
A data engineering team is designing a modern data warehouse using Azure Synapse Analytics. They want to follow a lakehouse architecture where raw data is stored in its native format and then processed and curated for reporting. Which component in Azure Synapse Analytics is primarily used to store raw data in its original format without requiring a schema?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Data Lake Storage Gen2
Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct component because it provides a scalable, hierarchical file system that can store raw data in any native format (e.g., CSV, JSON, Parquet) without requiring a predefined schema. This aligns with the lakehouse architecture's requirement to ingest and persist raw data as-is before any transformation or curation.
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.
✗
Dedicated SQL pool
Why it's wrong here
A Dedicated SQL pool stores data in relational tables with a predefined schema, not raw data in original format.
✗
Serverless SQL pool
Why it's wrong here
A Serverless SQL pool is a query engine that reads data from the data lake; it does not store data itself.
✗
Synapse Pipeline
Why it's wrong here
Synapse Pipeline is an orchestration service for data movement and transformation, not a storage layer.
✓
Data Lake Storage Gen2
Why this is correct
Azure Data Lake Storage Gen2 is the underlying storage that holds raw data in its native format, supporting the lakehouse architecture.
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 the role of a Serverless SQL pool (which can query raw data) with the actual storage layer, leading them to incorrectly select Option B instead of recognizing that ADLS Gen2 is the persistent, schema-less storage component.
Detailed technical explanation
How to think about this question
ADLS Gen2 combines Azure Blob Storage with a hierarchical namespace, enabling POSIX-compliant access control and directory operations. In a lakehouse architecture, raw data lands in ADLS Gen2 as files (e.g., in a 'bronze' zone), and later processing layers (e.g., 'silver' and 'gold') apply schema-on-read using tools like Serverless SQL or Spark. This decouples storage from compute, allowing multiple engines to query the same raw data without prior schema definition.
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
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.
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: Data Lake Storage Gen2 — Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct component because it provides a scalable, hierarchical file system that can store raw data in any native format (e.g., CSV, JSON, Parquet) without requiring a predefined schema. This aligns with the lakehouse architecture's requirement to ingest and persist raw data as-is before any transformation or curation.
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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