DP-900 Describe an analytics workload on Azure Practice Question
Your company has a Power BI report that uses DirectQuery to Azure SQL Database. Users report that the report is slow when multiple users access it simultaneously. The database is underprovisioned. Which action should you take to improve performance without changing the report design?
⚠ Common exam trap
Watch out — candidates often confuse performance tuning at the database level (scaling up) with caching or data import strategies, overlooking the explicit constraint that the report design must remain unchanged and that the database is the bottleneck.
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
✓
Scale up the Azure SQL Database to a higher service tier.
The root cause is an underprovisioned Azure SQL Database, which cannot handle the concurrent query load from multiple Power BI users using DirectQuery. Scaling up to a higher service tier (e.g., from S2 to S3 or a DTU-based tier) increases the database's DTUs (Database Transaction Units), directly improving throughput and reducing query latency without altering the report design.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable query caching in Power BI Premium.
Why it's wrong here
Query caching stores result sets for dashboards and reports in Premium capacity, but it only helps subsequent loads of the same visuals; the first time a user opens the report (or when data changes invalidate the cache), DirectQuery still sends queries to the source. It does not increase the source database's ability to handle concurrent connections or processing load, so it cannot fix underlying throughput limits.
- ✗
Change the report to use Import mode instead of DirectQuery.
Why it's wrong here
Switching to Import mode would copy data into Power BI and shift query load away from the source, but it requires redesigning the dataset, setting up refresh schedules, and may violate real-time data requirements or exceed memory limits on the capacity. It is a design change with significant trade-offs (data freshness, storage) and is not a quick fix for concurrency issues.
- ✓
Scale up the Azure SQL Database to a higher service tier.
Why this is correct
A higher service tier (e.g., more DTUs or vCores) increases the database's computing resources, which directly raises the number of concurrent DirectQuery queries that can be processed without timeout or throttling. Since the bottleneck is the source database's capacity to handle parallel query execution, scaling up addresses the root cause of concurrency-related performance degradation.
- ✗
Add indexes to the tables used in the report.
Why it's wrong here
Indexes reduce the time each individual query takes by enabling faster seeks, but they do not increase the database's capacity to run many queries simultaneously; concurrency limits are typically due to CPU, memory, or connection pool constraints, not per-query speed. While indexing can free up resources slightly, it does not resolve the core problem when the issue is a flood of concurrent DirectQuery connections.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
Related to this question
Learn chapter
Azure SQL Services
Key term
Report
A report in Azure data services is a structured output that summarizes, visualizes, or details data stored in cloud databases or data warehouses, often used for business intelligence and monitoring.
Key term
Power BI
Power BI is a Microsoft business analytics tool that transforms raw data into interactive visual reports and dashboards for informed decision-making.
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