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

SectionWeightObjectives
Topic 1: Data Processing & Transformations31%- Query optimization and performance
  • 1. Understanding query plans
  • 2. Optimization strategies
- Data transformation techniques
  • 1. Complex data processing logic
  • 2. DataFrame operations and transformations
  • 3. Aggregations, joins, and window functions
Topic 2: Data Governance & Quality11%- Data quality and reliability
  • 1. Schema enforcement and evolution
  • 2. Data validation and quality checks
- Unity Catalog implementation
  • 1. Data governance model
  • 2. Permissions and access control
Topic 3: Development and Ingestion30%- Notebook development fundamentals
  • 1. Data exploration and validation
  • 2. Using PySpark and Spark SQL
- Data ingestion patterns and methods
  • 1. Batch and streaming ingestion
  • 2. Delta Lake basics and usage
  • 3. Connecting to external data sources
Topic 4: Databricks Intelligence Platform10%- Platform architecture and core concepts
  • 1. Data layout and optimization: partitioning, file sizing, caching
  • 2. Compute options: clusters, SQL warehouses, serverless
  • 3. Workspace navigation and management
Topic 5: Productionizing Data Pipelines18%- Monitoring and troubleshooting
  • 1. Pipeline reliability and recovery
  • 2. Logging and error handling
- Deployment and CI/CD
  • 1. Databricks Asset Bundles
  • 2. Version control integration
- Workflow orchestration
  • 1. Lakeflow Jobs creation and management
  • 2. Scheduling, triggers, and dependencies

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q277-Q282):

NEW QUESTION # 277
Which SQL keyword can be used to convert a table from a long format to a wide format?

Answer: D


NEW QUESTION # 278
Identify how the count_if function and the count where x is null can be used.
Consider a table random_values with below data.
What would be the output of below query?
select count_if(col1 > 1) as count_a, count(*) as count_b,count(col1)
as count_c from random_values
col1
0
1
2
NULL
2
3

Answer: D


NEW QUESTION # 279
A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).
Which of the following code blocks creates this SQL UDF?

Answer: C

Explanation:
https://www.databricks.com/blog/2021/10/20/introducing-sql-user-defined-functions.html


NEW QUESTION # 280
A data engineer wants to read only a subset of columns from a Delta table to reduce memory usage and improve performance. Which Spark DataFrame operation should be used?

Answer: C


NEW QUESTION # 281
A data engineering team needs to incrementally ingest customer transactions from a SaaS application into the Databricks Data Intelligence Platform with the following capabilities:
Built-in change data capture, including updates and deletes
Automatic schema evolution
Serverless execution with retries and minimal maintenance
OAuth support and basic monitoring
Which solution meets all the requirements?

Answer: B

Explanation:
Option D satisfies the requirements because a Lakeflow Connect managed SaaS connector provides source-specific authentication, incremental ingestion, schema evolution, and automated retries as managed capabilities. Managed connectors use serverless infrastructure and publish governed destination tables that can be processed downstream with Lakeflow Spark Declarative Pipelines. This avoids custom code for OAuth token handling, API pagination, CDC state management, retry behavior, and schema-change recovery. Option A still requires the engineering team to implement and maintain CDC and operational logic. Options B and C place most authentication, schema evolution, change tracking, and failure recovery responsibilities in custom notebooks or jobs, conflicting with the minimal-maintenance requirement. Therefore, the fully managed connector described in option D is the only solution that delivers the requested ingestion and operational behavior as an integrated platform capability.


NEW QUESTION # 282
......

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