Databricks Databricks-Certified-Data-Engineer-Associate Dumps with Practice Test Questions [2026]

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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:

SectionWeightObjectives
Data Governance & Quality11%- Data quality and reliability
  • 1. Schema enforcement and evolution
  • 2. Data validation and quality checks
- Unity Catalog implementation
  • 1. Data governance model
  • 2. Permissions and access control
Databricks Intelligence Platform10%- Platform architecture and core concepts
  • 1. Workspace navigation and management
  • 2. Data layout and optimization: partitioning, file sizing, caching
  • 3. Compute options: clusters, SQL warehouses, serverless
Data Processing & Transformations31%- Data transformation techniques
  • 1. DataFrame operations and transformations
  • 2. Complex data processing logic
  • 3. Aggregations, joins, and window functions
- Query optimization and performance
  • 1. Optimization strategies
  • 2. Understanding query plans
Productionizing Data Pipelines18%- Workflow orchestration
  • 1. Lakeflow Jobs creation and management
  • 2. Scheduling, triggers, and dependencies
- Deployment and CI/CD
  • 1. Version control integration
  • 2. Databricks Asset Bundles
- Monitoring and troubleshooting
  • 1. Pipeline reliability and recovery
  • 2. Logging and error handling
Development and Ingestion30%- Data ingestion patterns and methods
  • 1. Connecting to external data sources
  • 2. Batch and streaming ingestion
  • 3. Delta Lake basics and usage
- Notebook development fundamentals
  • 1. Using PySpark and Spark SQL
  • 2. Data exploration and validation

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q275-Q280):

NEW QUESTION # 275
A Lakeflow Jobs workflow fails at the last task because of an error in a notebook task. This workflow is scheduled to run daily. The data engineer fixes the notebook and wants to rerun the pipeline. This workflow is very compute-intensive and expensive to run. Which action should the data engineer take in order to minimize downtime and compute cost?

Answer: A

Explanation:
Repair run allows rerunning only the failed task and any dependent tasks instead of executing the entire workflow again, minimizing compute cost and downtime while preserving the original run context.


NEW QUESTION # 276
Which query is performing a streaming hop from raw data to a Bronze table?

Answer: C


NEW QUESTION # 277
A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to a data analytics dashboard for a retail use case. The job has a Databricks SQL query that returns the number of store-level records where sales is equal to zero. The data engineer wants their entire team to be notified via a messaging webhook whenever this value is greater than 0.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of stores with $0 in sales is greater than zero?

Answer: B

Explanation:
A webhook alert destination is a notification destination that allows Databricks to send HTTP POST requests to a third-party endpoint when an alert is triggered. This enables the data engineer to integrate Databricks alerts with their preferred messaging or collaboration platform, such as Slack, Microsoft Teams, or PagerDuty.
To set up a webhook alert destination, the data engineer needs to create and configure a webhook connector in their messaging platform, and then add the webhook URL to the Databricks notification destination. After that, the data engineer can create an alert for their Databricks SQL query, and select the webhook alert destination as the notification destination. The alert can be configured with a custom condition, such as when the number of stores with $0 in sales is greater than zero, and a custom message template, such as "Alert:
{number_of_stores} stores have $0 in sales". The alert can also be configured with a recurrence interval, such as every hour, to check the query result periodically. When the alert condition is met, the data engineer and their team will receive a notification via the messaging webhook, with the custom message and a link to the Databricks SQL query. The other options are either not suitable for sending notifications via a messaging webhook (A, B, E), or not suitable for sending recurring notifications . References: Databricks Documentation -Manage notification destinations, Databricks Documentation - Create alerts for Databricks SQL queries, Databricks Documentation - Configure alert conditions and messages.


NEW QUESTION # 278
A data engineer is working on a Databricks project that utilizes cloud storage. The data engineer wants to load several JSON files from containers on a storage account as soon as the file arrives within the storage account. Which syntax should the data engineer follow to first load the files into a dataframe and check that it is working as expected using Python?

Answer: A

Explanation:
To automatically ingest JSON files as soon as they arrive in cloud storage, the correct syntax is to use Auto Loader with spark.readStream.format("cloudFiles").option("cloudFiles.format",
"json").load("/input/path"). This enables continuous ingestion of new files into a streaming dataframe.


NEW QUESTION # 279
A data engineer is running a Spark job that processes data stored in Delta format. The engineer wants to reduce the number of files by compacting smaller files into larger ones to improve query performance. Which Delta Lake command performs this operation?

Answer: A


NEW QUESTION # 280
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