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

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

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q81-Q86):

NEW QUESTION # 81
Which of the following queries is performing a streaming hop from raw data to a Bronze table?

Answer: E


NEW QUESTION # 82
A data engineer is migrating pipeline tasks to reduce operational toil. The workspace used Unity Catalog and is in a region that supports serverless. The engineer wants Databricks to auto-select instance types, manage scaling, apply Photon, and handle runtime upgrades automatically for job runs.
How should the data engineer meet this requirement while adhering to Databricks constraints?

Answer: D

Explanation:
Serverless compute for workflows allows Databricks to automatically manage instance selection, scaling, Photon enablement, and runtime upgrades for job runs, provided Unity Catalog is enabled and the workspace region supports serverless.


NEW QUESTION # 83
A data engineer has left the organization. The data team needs to transfer ownership of the data engineer's Delta tables to a new data engineer. The new data engineer is the lead engineer on the data team.
Assuming the original data engineer no longer has access, which of the following individuals must be the one to transfer ownership of the Delta tables in Data Explorer?

Answer: E


NEW QUESTION # 84
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: D

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


NEW QUESTION # 85
Which of the following tools is used by Auto Loader process data incrementally?

Answer: B

Explanation:
Auto Loader provides a Structured Streaming source called cloudFiles that can process new data files as they arrive in cloud storage without any additional setup. Auto Loader uses a scalable key-value store to track ingestion progress and ensure exactly-once semantics. Auto Loader can ingest various file formats and load them into Delta Lake tables. Auto Loader is recommended for incremental data ingestion with Delta Live Tables, which extends the functionality of Structured Streaming and allows you to write declarative Python or SQL code to deploy a production-quality data pipeline. References: What is Auto Loader?, What is Auto Loader? | Databricks on AWS, Solved: How does Auto Loader ingest data? - Databricks - 5629


NEW QUESTION # 86
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