Describe considerations for working with non-relational data on Azure →easyMultiple ChoiceObjective-mapped
DP-900 Practice Question: Describe considerations for working with non-relational data on Azure
You are storing log files from multiple applications in Azure Blob Storage. Each log file is a text file with timestamp data. You need to query logs for a specific date range using SQL. Which Azure service can query these files directly?
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 Synapse Serverless SQL
Azure Synapse Serverless SQL can query text files in Azure Blob Storage using OPENROWSET with the CSV or text file format, allowing SQL queries over log files. Option A (Azure Stream Analytics) is for real-time streaming, not ad-hoc SQL batch queries. Option B (Azure Data Lake Storage) is a storage service, not a query engine. Option D (Azure Analysis Services) is for semantic models and OLAP, not direct file querying.
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 Stream Analytics
Why it's wrong here
Azure Stream Analytics is a real-time event processing engine, not an interactive batch query service. It ingests live data streams from sources like Event Hubs or IoT Hub and writes results to sinks, but it cannot execute ad-hoc T-SQL queries against static log files already stored in blob storage. For querying existing log files, Synapse Serverless SQL is the appropriate tool.
- ✗
Azure Data Lake Storage
Why it's wrong here
Azure Data Lake Storage is a hierarchical, scalable file system built on Blob Storage, offering POSIX-like access and security for big data analytics. It is purely a storage layer—it does not include a query engine that can execute T-SQL against files. To query the log files with T-SQL, you must use a compute service like Synapse Serverless SQL, which can read from Data Lake Storage or Blob Storage externally.
- ✓
Azure Synapse Serverless SQL
Why this is correct
Azure Synapse Serverless SQL is an on-demand query engine that uses T-SQL and OPENROWSET to query files directly from Blob Storage or Azure Data Lake Storage Gen2 without provisioning dedicated compute. It supports various file formats such as Parquet, CSV, and JSON, and charges per query based on bytes scanned. This enables interactive, schema-on-read analysis of log files, exactly matching the requirement to query stored log files.
- ✗
Azure Analysis Services
Why it's wrong here
Azure Analysis Services is an OLAP modeling engine used to build multidimensional or tabular semantic models for business intelligence dashboards. It does not query raw files directly; you must first import and load data into the model, which then serves pre-aggregated results. For direct T-SQL queries over log files stored in blob storage, Synapse Serverless SQL is the correct service, not Analysis Services.
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
Data lake
A data lake is a centralized storage repository that holds vast amounts of raw data in its native format until it is needed for analysis.
Key term
Azure Stream Analytics
Azure Stream Analytics is a fully managed, real-time data processing service that analyzes and transforms high volumes of streaming data from various sources to deliver low-latency insights and trigger actions.
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