Databricks Data Engineer Professional Exam Practice Questions - ANALYSIS NOV 2023 (25Q)

Introduction

This tutorial is designed to help you prepare for the Databricks Certified Data Engineer Professional certification exam. It covers key topics and practice questions relevant to the exam, focusing on advanced data engineering tasks using the Databricks platform. By the end of this guide, you'll have a clearer understanding of the exam's structure and the core concepts you need to master.

Step 1: Understand the Exam Structure

Familiarize yourself with the breakdown of topics covered in the exam to focus your studies effectively.

• Databricks Tooling: 20%
• Data Processing: 30%
• Data Modeling: 20%
• Security and Governance: 10%
• Monitoring and Logging: 10%
• Testing and Deployment: 10%

Step 2: Master Key Concepts of Delta Lake

Delta Lake is a critical component of the Databricks platform. Understanding its features will help you answer exam questions effectively.

Key Points:

• Delta Lake uses transaction logs to manage data updates.
• When querying a Delta table, the count of records is derived from the transaction logs, not by scanning data files.
• Managed tables remove both the table reference and underlying data upon dropping.

Step 3: Familiarize Yourself with Data Processing and ETL Pipelines

Building optimized and cleaned ETL pipelines is a significant part of this exam.

Practical Tips:

• Utilize Spark for parallel data processing to enhance performance.
• Understand the importance of partitioning for performance in data storage formats like Parquet.

Example Code:

To create a Delta table, you might use the following SQL command:

CREATE TABLE my_table USING DELTA
LOCATION '/mnt/my_data';

Step 4: Know Security and Governance Practices

Security and data governance are essential for a successful data engineering process.

Key Points:

• Understand access control mechanisms to manage permissions effectively.
• Be aware that tables can be configured as external (unmanaged) by specifying the location during creation.

Step 5: Implement Monitoring and Testing Strategies

Monitoring data pipelines is crucial for ensuring reliability and performance.

Key Points:

• Use Databricks' built-in monitoring tools to track the performance of your jobs.
• Ensure that data quality tests are integrated into your ETL workflows to catch issues early.

Step 6: Learn About Advanced Data Modeling Concepts

Modeling data effectively is necessary for building a robust lakehouse architecture.

Practical Tips:

• Familiarize yourself with dimensional modeling and schema design principles.
• Understand the implications of data cardinality when designing your models, especially for free-text fields.

Step 7: Prepare for Common Exam Scenarios

Review practice questions to familiarize yourself with the exam format and types of questions.

Example Scenario:

When tasked with ensuring no late-arriving records cause duplicates, consider using an insert-only merge strategy that checks for existing records before inserting.

Conclusion

To succeed in the Databricks Certified Data Engineer Professional exam, focus on understanding the exam structure, mastering Delta Lake, and being well-versed in data processing, security, monitoring, and modeling concepts. Regularly practice with exam-style questions and scenarios to reinforce your knowledge. Good luck with your preparation, and consider utilizing additional resources like the related playlists for further learning.