Quick Answer
The answer is Azure Data Lake Storage Gen2 (ADLS Gen2) because it uniquely combines a hierarchical namespace with Azure Blob Storage, allowing you to store structured, semi-structured, and unstructured data in a single data lake while supporting fast, SQL-like queries on structured data without moving it to a separate store. This is achieved through the ABFS driver, which enables high-performance analytics directly from query engines like Azure Synapse SQL and Apache Spark. On the DP-900 exam, this question tests your understanding of how ADLS Gen2 differs from standard Blob Storage—the key trap is choosing Azure Synapse Analytics alone, which is a query service, not a storage service. Remember that ADLS Gen2 is the storage layer that makes fast queries possible; Synapse is the tool that runs them. A helpful memory tip: think of ADLS Gen2 as “Blob Storage with a brain”—the hierarchical namespace organizes files like folders, enabling the fast, directory-level queries that a flat blob container cannot.
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 company wants to build a data lake on Azure for storing structured, semi-structured, and unstructured data. The solution must support fast queries on structured data without moving data to a separate store. Which Azure service should they use?
Azure Blob Storage
Why wrong: Blob Storage lacks hierarchical namespace and advanced analytics features.
Azure SQL Database
Why wrong: SQL Database is relational and not suitable for semi-structured/unstructured data.
Azure Data Lake Storage Gen2
ADLS Gen2 combines blob storage with a hierarchical namespace and is optimized for analytics.
Azure Cosmos DB
Why wrong: Cosmos DB is a NoSQL database, not a data lake.
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 Data Lake Storage Gen2
Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines a hierarchical namespace with Azure Blob Storage, enabling both a data lake for unstructured and semi-structured data and fast, SQL-like queries on structured data using Azure Synapse Analytics or PolyBase without moving data. It supports the ABFS (Azure Blob File System) driver for high-performance analytics and integrates directly with query engines like Apache Spark and Azure Synapse SQL.
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 Blob Storage
Why it's wrong here
Blob Storage lacks hierarchical namespace and advanced analytics features.
Azure SQL Database
Why it's wrong here
SQL Database is relational and not suitable for semi-structured/unstructured data.
Azure Data Lake Storage Gen2
Why this is correct
ADLS Gen2 combines blob storage with a hierarchical namespace and is optimized for analytics.
Related concept
Read the scenario before looking for a memorised answer.
Azure Cosmos DB
Why it's wrong here
Cosmos DB is a NoSQL database, not a data lake.
Common exam traps
The trap here is that candidates often pick Azure Blob Storage because it is the underlying storage for ADLS Gen2, but they miss that ADLS Gen2's hierarchical namespace is required for fast, directory-level queries and direct SQL access without moving data.
Detailed technical explanation
ADLS Gen2 leverages a hierarchical namespace that allows for POSIX-like access control and directory operations, which is critical for managing large-scale data lakes. Under the hood, it uses the ABFS driver to enable direct access from compute services like Azure Synapse, allowing queries such as SELECT * FROM OPENROWSET(BULK ...) to run directly on Parquet or CSV files stored in the lake. A real-world scenario is a retail company storing clickstream logs (unstructured), customer profiles (semi-structured JSON), and sales transactions (structured CSV) in the same ADLS Gen2 account, then running fast aggregation queries on the sales data via Synapse without any data duplication.
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: Azure Data Lake Storage Gen2 — Azure Data Lake Storage Gen2 (ADLS Gen2) is the correct choice because it combines a hierarchical namespace with Azure Blob Storage, enabling both a data lake for unstructured and semi-structured data and fast, SQL-like queries on structured data using Azure Synapse Analytics or PolyBase without moving data. It supports the ABFS (Azure Blob File System) driver for high-performance analytics and integrates directly with query engines like Apache Spark and Azure Synapse SQL.
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
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