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Exam Code:Databricks Certified Data Engineer Professional

Exam Name:Databricks Certified Data Engineer Professional Exam

Q&A:337 Q&As

Updated: 04-27-2024

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Prepare for success in the Databricks Certified Data Engineer Professional Exam with ExamGood's expertly designed study materials. Elevate your data engineering skills and propel your career.

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Databricks Certified Data Engineer Professional

The Databricks Certified Data Engineer Professional certification exam evaluates an individual's proficiency in using Databricks for advanced data engineering tasks, including working with Apache Spark™, Delta Lake, MLflow, and the Databricks CLI and REST API. It also tests the ability to build optimized ETL pipelines, model data into a lakehouse, and ensure secure and reliable data pipelines. Passing this exam demonstrates the capability to perform advanced data engineering tasks using Databricks and associated tools.

The exam covers:

1. Databricks Tooling – 20%

2. Data Processing – 30%

3. Data Modeling – 20%

4. Security and Governance – 10%

5. Monitoring and Logging – 10%

6. Testing and Deployment – 10%

Assessment Details

Databricks offers the Databricks Certified Data Engineer Professional certification, which is a proctored exam consisting of 60 multiple-choice questions. The exam has a time limit of 120 minutes and a registration fee of $200 (with a 50% discount for Databricks partners). It is delivered online and is valid for 2 years. Recertification is required to maintain certification status. The exam may include unscored items for statistical purposes, which do not affect the final score.

Related Training

Databricks offers instructor-led and self-paced courses for advanced data engineering with Databricks, as well as a certification overview course for the Databricks Certified Data Engineer Professional Exam.

Getting Ready for the Exam

To become a Databricks Certified Data Engineer Professional, follow these steps: review the exam guide, take related training, register for the exam, check technical requirements, review the exam guide again, study to fill in any gaps, and finally, take the exam. Note that code examples will be in Python, but references to Delta Lake functionality will be in SQL.

Training Material

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