100% Pass Quiz 2026 Databricks Certified-Data-Engineer-Professional: Databricks Certified Data Engineer Professional Accurate Complete Exam Dumps

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

SectionWeightObjectives
Data Sharing and Federation~8%- Configure Delta Sharing and Lakehouse Federation
Monitoring, Logging, and Troubleshooting~8%- Diagnose common pipeline and job failures
- Use Spark UI, Query Profiler, and system tables
Data Transformation, Cleansing, and Quality~12%- Enforce data quality and quarantine bad data
- Apply advanced Spark transformations
Data Modeling~10%- Apply dimensional modeling techniques
- Design scalable Delta Lake schemas and clustering
CI/CD, Testing, and Deployment~6%- Deploy with Declarative Automation Bundles, CLI, and REST API
- Implement testing and deployment pipelines
Developing Code for Data Processing using Python and SQL~22%- Manage dependencies, libraries, and UDFs
- Implement scalable Python/SQL code and project structures
- Build pipelines with Lakeflow Spark Declarative Pipelines and Auto Loader
Cost and Performance Optimization~13%- Leverage system tables and observability tools
- Optimize queries, clusters, and storage
Security and Governance~10%- Implement row-level security, column masking, and compliance
- Manage Unity Catalog permissions and ACLs
Streaming Workloads and Change Data Capture~11%- Apply AUTO CDC APIs and exactly-once semantics
- Implement reliable streaming pipelines

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Databricks Certified Data Engineer Professional Sample Questions (Q130-Q135):

NEW QUESTION # 130
Each configuration below is identical to the extent that each cluster has 400 GB total of RAM, 160 total cores and only one Executor per VM.
Given a job with at least one wide transformation, which of the following cluster configurations will result in maximum performance?

Answer: A

Explanation:
https://docs.databricks.com/en/clusters/cluster-config-best-practices.html


NEW QUESTION # 131
The data architect has mandated that all tables in the Lakehouse should be configured as external Delta Lake tables.
Which approach will ensure that this requirement is met?

Answer: D

Explanation:
This is the correct answer because it ensures that this requirement is met. The requirement is that all tables in the Lakehouse should be configured as external Delta Lake tables. An external table is a table that is stored outside of the default warehouse directory and whose metadata is not managed by Databricks. An external table can be created by using the location keyword to specify the path to an existing directory in a cloud storage system, such as DBFS or S3. By creating external tables, the data engineering team can avoid losing data if they drop or overwrite the table, as well as leverage existing data without moving or copying it.


NEW QUESTION # 132
A senior data engineer is planning large-scale data workflows. The current task is to identify the considerations that form a foundation for creating scalable data models that are essential for effective management of large datasets. The data engineering team has identified the core capabilities as part of a scalable data model to build a modern data platform and provided their reasoning for considering Delta Lake for review. The senior data engineer is responsible for identifying the recommendations that are not valid. Which key features can be ignored while evaluating Delta Lake?

Answer: C

Explanation:
Delta Lake includes built-in capabilities for monitoring, auditing, and troubleshooting through transaction logs, history, and tight integration with the Databricks platform. Therefore, limited support for monitoring and troubleshooting is not a valid concern when evaluating Delta Lake and can be ignored.


NEW QUESTION # 133
A data engineering workspace was automatically enabled for Unity Catalog, creating a workspace catalog. New team members report they can create tables in the default schema but cannot access table in other schemas within the same workspace catalog. Why are the new team members unable to access tables in other schemas?

Answer: C

Explanation:
When a workspace catalog is automatically created, new users are granted USE CATALOG and limited privileges on the default schema only. Access to other schemas requires explicit grants, so users cannot see or query tables in those schemas without additional permissions.


NEW QUESTION # 134
A data engineer has created a transactions Delta table on Databricks that should be used by the analytics team. The analytics team wants to use the table with another tool that requires Apache Iceberg format. What should the data engineer do?

Answer: A

Explanation:
Delta Lake introduced Delta Universal Format (Delta UniForm), which allows seamless interoperability between Delta Lake and Apache Iceberg. This means a Delta table can be converted into an Iceberg table while maintaining Delta capabilities.


NEW QUESTION # 135
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