Databricks Certified Data Engineer Associate Exam Practice Questions - ANALYSIS SEP 2023 (44Q)

Introduction

This tutorial provides a comprehensive guide on preparing for the Databricks Certified Data Engineer Associate exam. It covers essential concepts, common pitfalls, and practical strategies based on analysis of recent exam questions. By understanding the exam structure and key topics, you can enhance your chances of passing the certification.

Step 1: Understand the Exam Structure

• Exam Overview: The exam consists of 45 questions with a time limit of 90 minutes.
• Question Types: Expect multiple-choice questions focused on practical application.
• Key Topics:
  • Databricks Lakehouse Platform (24%)
  • ELT with Spark SQL and Python (29%)
  • Incremental Data Processing (22%)
  • Production Pipelines (16%)
  • Data Governance (9%)

Step 2: Familiarize Yourself with Core Concepts

• Databricks Lakehouse: Understand its architecture and capabilities, focusing on data engineering tasks.
• Apache Spark™ SQL: Gain practical experience in writing SQL queries and managing data transformations.
• ETL Pipelines: Learn how to build and optimize ETL pipelines using Databricks.

Step 3: Practice Key Command Types

Familiarize yourself with commands related to data manipulation:

• Grant Permissions: Know how to grant usage and administrative privileges on databases.

  GRANT USAGE ON DATABASE customers TO `team`;
  

• Table Creation and Management: Understand how to create and manage tables in Delta Lake.

  CREATE TABLE new_table USING delta LOCATION '/path/to/location';
  

Step 4: Learn Incremental Data Processing

• Auto Loader: Use Auto Loader to process new files automatically.
• Structured Streaming: Familiarize yourself with structured streaming queries and their configurations.

  df.writeStream.format("delta").outputMode("append").start("/path/to/delta");
  

Step 5: Explore Data Quality Management

• Expectations: Set data quality expectations using Delta Live Tables to monitor incoming data.
• Alerts: Configure alerts to notify teams when data quality thresholds are breached.

Step 6: Understand the Medallion Architecture

• Bronze, Silver, and Gold Tables: Know the purpose of each layer in the data pipeline:
  • Bronze: Raw data
  • Silver: Cleaned data
  • Gold: Business-ready data with aggregations

Step 7: Review Performance Optimization Techniques

• Cluster Management: Use job clusters for specific tasks to improve performance and reduce startup times.
• SQL Endpoint Management: Optimize SQL endpoints to minimize costs and enhance performance.

Step 8: Study Real-World Applications

• Analyze real-world scenarios, such as:
  • Managing data ingestion from various sources
  • Automating data quality checks
  • Creating dashboards and reports using Databricks SQL

Conclusion

Preparation for the Databricks Certified Data Engineer Associate exam requires a solid understanding of the Lakehouse architecture, practical experience with Spark SQL, and awareness of data governance practices. Focus on key concepts, practice hands-on tasks, and familiarize yourself with the exam structure to enhance your chances of success. Consider exploring additional resources like documentation and practice exams to solidify your knowledge. Good luck!