DP-200 Azure Data Monitoring and Optimization 1 — Questions and Answers
Question 1: Which Azure tool provides a unified monitoring experience for metrics, logs, and alerts across Azure data services?
- Azure Service Health
- Azure Monitor (Correct answer)
- Azure Advisor
- Azure Cost Management
Correct answer: Azure Monitor
Azure Monitor collects, analyzes, and acts on telemetry from Azure resources, providing metrics, logs, alerts, and dashboards in a single platform.
Question 2: In Azure SQL Database, what is the purpose of Query Store?
- To cache frequently executed query results
- To capture query execution plans and runtime statistics for performance troubleshooting (Correct answer)
- To store parameterized queries as stored procedures
- To replicate queries to a secondary replica
Correct answer: To capture query execution plans and runtime statistics for performance troubleshooting
Query Store persists query execution plans, runtime statistics, and wait statistics over time, enabling analysis of query performance regressions.
Question 3: What Azure SQL Database feature automatically identifies performance recommendations such as missing indexes or plan regression?
- Query Store
- Automatic Tuning (Correct answer)
- Extended Events
- Dynamic Management Views (DMVs)
Correct answer: Automatic Tuning
Automatic Tuning in Azure SQL Database monitors workloads and can automatically create missing indexes, drop unused indexes, and correct plan regressions.
Question 4: In Azure Synapse Analytics dedicated SQL pool, which distribution type should be used for small dimension tables to avoid data movement during joins?
- Hash distribution
- Round-robin distribution
- Replicated distribution (Correct answer)
- Partitioned distribution
Correct answer: Replicated distribution
Replicated tables store a full copy on every compute node, eliminating data movement when joining small dimension tables with large fact tables.
Question 5: What is the purpose of result-set caching in Azure Synapse Analytics dedicated SQL pool?
- To store intermediate ETL results in ADLS
- To return cached results for repeated identical queries without re-executing the computation (Correct answer)
- To compress query results before returning to the client
- To distribute query load across nodes
Correct answer: To return cached results for repeated identical queries without re-executing the computation
Result-set caching stores the output of a query and serves the same result for subsequent identical queries, dramatically reducing latency for repeated BI queries.
Question 6: Which Azure Cosmos DB metric should you monitor to detect when your provisioned throughput is being throttled?
- Total Request Units consumed
- HTTP 429 (Request Rate Too Large) error rate (Correct answer)
- Average document size in bytes
- Number of physical partitions
Correct answer: HTTP 429 (Request Rate Too Large) error rate
HTTP 429 errors in Cosmos DB indicate that requests are exceeding provisioned RU/s, causing the service to throttle and retry operations.
DP-200 Azure Data Monitoring and Optimization 1
Which Azure tool provides a unified monitoring experience for metrics, logs, and alerts across Azure data services?