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The Databricks Databricks-Certified-Professional-Data-Engineer exam is ideal for data engineers who want to demonstrate their expertise in designing, building, and maintaining big data processing pipelines using Databricks. Databricks Certified Professional Data Engineer Exam certification exam is tailored to the specific roles and responsibilities of a data engineer, and it covers a range of topics, including data ingestion, data transformations, data storage, and data analysis. By passing the exam, candidates can demonstrate their proficiency in using Databricks to solve complex big data challenges.
Reference: https://www.databricks.com/learn/certification/data-engineer-professional
The DCPDE exam covers various topics, including data engineering, data architecture, and data processing. Databricks-Certified-Professional-Data-Engineer exam is designed to evaluate the candidate's ability to use Databricks to design and implement data processing solutions. Databricks-Certified-Professional-Data-Engineer exam also evaluates the candidate's ability to design and implement data pipelines, optimize Spark jobs, and troubleshoot data processing issues.
Databricks Databricks-Certified-Professional-Data-Engineer Exam Overview:
| Certification Vendor: | Databricks |
| Exam Name: | Databricks Certified Professional Data Engineer Exam |
| Exam Number: | Databricks-Certified-Professional-Data-Engineer |
| Exam Format: | Multiple Choice |
| Related Certifications: | Databricks Certified Associate Data Engineer |
| Available Languages: | English, Japanese, Portuguese (Brazil), Korean |
| Real Exam Qty: | 59 |
| Exam Duration: | 120 minutes |
| Exam Price: | USD 200 |
| Passing Score: | 70% |
| Certificate Validity Period: | 2 years |
| Recommended Training: | Databricks Data Engineer Professional Training |
| Exam Registration: | Databricks Official Certification Registration |
| Sample Questions: | Databricks Databricks-Certified-Professional-Data-Engineer Sample Questions |
| Exam Way: | Online proctored or onsite test center |
| Pre Condition: | No mandatory prerequisites; 1+ year hands-on experience and related training highly recommended |
| Official Syllabus URL: | https://www.databricks.com/learn/certification/data-engineer-professional |
Databricks Databricks-Certified-Professional-Data-Engineer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Sharing and Federation | 5% | - Unity Catalog data sharing - Cross-workspace and cross-cloud access |
| Topic 2: Debugging and Deploying | 10% | - Troubleshooting pipelines and errors - Deployment using bundles, CLI, and APIs - CI/CD and DevOps practices |
| Topic 3: Data Governance | 7% | - Unity Catalog management - Data lineage and metadata tracking - Policy enforcement |
| Topic 4: Data Ingestion & Acquisition | 7% | - Auto Loader and streaming ingestion - Connecting to diverse data sources - Schema inference and evolution |
| Topic 5: Monitoring and Alerting | 10% | - Setting up alerts and notifications - Performance and health monitoring - Pipeline observability and logging |
| Topic 6: Data Transformation, Cleansing, and Quality | 10% | - Data validation and quality checks - Standardization and normalization - Handling missing or inconsistent data |
| Topic 7: Ensuring Data Security and Compliance | 10% | - Compliance standards implementation - Access control and permissions - Data encryption and masking |
| Topic 8: Developing Code for Data Processing using Python and SQL | 22% | - Integration with Databricks APIs and tools - Batch and incremental processing logic - Data transformation and aggregation |
| Topic 9: Cost & Performance Optimisation | 13% | - Query optimization and caching - Cluster configuration and scaling - Storage optimization (partitioning, Z-order, indexing) |
| Topic 10: Data Modelling | 6% | - Schema design and management - Medallion Architecture implementation - Delta Lake table design |
By Winston
