Whether you’re a beginner or a seasoned data engineer, these quiz questions will help you evaluate and strengthen your understanding of Databricks Workflows and Pipelines—core features for automating data jobs in the Lakehouse.
🚀 Beginner Level (1–10)
- What is the primary purpose of Databricks Workflows?
A) Visualizing dashboards
B) Managing data permissions
C) Automating data and ML pipelines
D) Hosting web apps - What type of job can you schedule in a Databricks Workflow?
A) SQL query
B) Notebook
C) Python script
D) All of the above - True or False: Databricks Workflows support task dependencies.
True - What is a Databricks Job Cluster?
A) A shared cluster across the workspace
B) A cluster used only for a specific workflow run
C) A temporary cluster created for a job run
D) A legacy cluster type - Which of the following is NOT a valid task type in Databricks Workflows?
A) Notebook
B) Python script
C) Excel file
D) SQL query - What is the maximum number of retries you can configure per task in a workflow?
A) 1
B) 2
C) 10
D) Unlimited - True or False: Tasks in a workflow must always run sequentially.
False - What is used to define the order of execution between tasks in a workflow?
A) Tags
B) Schedules
C) Dependencies
D) Aliases - What is the default timeout for a task in Databricks Workflows?
A) 30 minutes
B) 1 hour
C) 3 hours
D) No timeout - Where can you monitor the status and logs of each task in a workflow?
A) SQL Editor
B) Unity Catalog
C) Jobs UI
D) FileStore
🔧 Intermediate Level (11–20)
- Which feature allows reusing and passing output between tasks in a Databricks Workflow?
A) Parameters
B) Task values
C) Secrets
D) Variables - Which is a valid trigger option for running workflows?
A) On Notebook Save
B) Scheduled time
C) Cluster restart
D) File download - How can you automate file-based workflows in Databricks?
A) Manual refresh
B) Unity Catalog policies
C) File arrival triggers via Auto Loader or Event Grid
D) DBFS mount - What does a task return if it runs successfully?
A) True
B) SUCCESS state
C) 0
D) OK - How do you pass parameters to a notebook task in Databricks?
A) Through secrets
B) Through cluster tags
C) Using the dbutils.widgets API
D) You can’t pass parameters - What is the primary difference between a Shared Cluster and Job Cluster in workflows?
A) Job clusters terminate automatically after use
B) Shared clusters are faster
C) Shared clusters support SQL only
D) Job clusters require Unity Catalog - Which permission is required to create a workflow job in Databricks?
A) Admin
B) Cluster Creator
C) Job Create permission
D) Repo Access - True or False: You can export workflow run logs to an external system (e.g., S3, Azure Blob).
True - Which UI component shows the full execution flow and task DAG in Databricks Workflows?
A) SQL Dashboard
B) Cluster tab
C) Jobs Run UI
D) Workspace sidebar - Which Databricks API is used to programmatically manage jobs?
A) REST 2.0 API
B) Jobs API 2.1
C) Unity Catalog API
D) Token API
💡 Advanced Level (21–25)
- What happens if a task fails and no retry policy is defined?
A) It continues to the next task
B) It retries 3 times by default
C) The entire job run fails
D) It restarts the cluster - What is the recommended way to share sensitive values between tasks?
A) Environment variables
B) JSON files
C) Databricks Secrets
D) Widgets - Which Databricks feature allows building declarative pipelines for batch ingestion?
A) Workflows
B) Delta Live Tables
C) Unity Catalog
D) MLflow - Delta Live Tables pipelines can be triggered using:
A) Unity Catalog only
B) Continuous or scheduled modes
C) Job Clusters only
D) Manual refresh only - True or False: Delta Live Tables provides built-in quality checks (expectations).
True
🆕 Bonus Questions
- What is the main advantage of using cluster reuse in Databricks workflows?
A) Increases logging capabilities
B) Better compatibility with Unity Catalog
C) Reduces start-up time and cost
D) Enables streaming jobs only - Which feature allows monitoring lineage and quality of Delta Live Table pipelines?
A) Databricks SQL
B) Feature Store
C) Pipeline Graph + Observability UI
D) Secrets Scope
Databricks Workflows and Delta Live Tables help simplify complex ETL, analytics, and ML pipelines. Understanding how to structure and automate these tasks can improve productivity and reliability.
Srinimf 