Databricks-DE-Pro Monitoring and Alerting Practice Question
A data engineer has deployed a Databricks SQL dashboard that queries a gold-layer table. The dashboard is used by executives every morning. The engineer wants to be notified if the dashboard's underlying query fails or returns zero rows, which would indicate a data pipeline issue. Which Databricks feature should they use to set up this notification?
⚠ Common exam trap
Test-takers frequently confuse job-level alerts with query-level alerts; job alerts monitor execution status, while SQL alerts monitor the actual data returned by a query.
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
✓
Databricks SQL alerts
Databricks SQL alerts are designed to monitor query results and trigger notifications based on conditions such as row count, value thresholds, or query failure. By creating an alert on the dashboard's query, the engineer can receive an email if the query fails or returns zero rows, ensuring timely awareness of data pipeline issues.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Databricks SQL alerts
Why this is correct
Databricks SQL alerts allow you to define a condition on a query result and trigger notifications when the condition is met. You can set an alert to fire if the query returns zero rows or fails, and configure email or webhook destinations. This directly addresses the need to monitor the dashboard's data freshness and query health.
- ✗
Job alerts on the Databricks job that refreshes the gold table
Why it's wrong here
Job alerts notify on job success or failure, not on query results or row counts. The gold table refresh job might succeed while producing an empty table. Job alerts cannot detect zero-row conditions in the dashboard query. They are one level removed from the dashboard's data quality.
- ✗
Cluster metrics and logging in the Clusters UI
Why it's wrong here
Cluster metrics show resource utilization, not query outcomes. They cannot detect that a dashboard query returned zero rows or failed. This option is unrelated to data content monitoring. Cluster metrics are for performance tuning, not for alerting on data pipeline issues.
- ✗
Delta Live Tables expectations
Why it's wrong here
DLT expectations are defined within a DLT pipeline to enforce data quality. They do not monitor external dashboards or queries. If the gold table is not produced by DLT, expectations are irrelevant. Even if it were, expectations operate during pipeline execution, not on dashboard queries.
About these practice questions
This Databricks-DE-Pro question is part of Courseiva's 267-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DE-Pro practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DE-Pro exam.