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

SectionObjectives
Databricks Lakehouse Platform Fundamentals- Clusters, notebooks, and basic Databricks environment usage
- Workspace, architecture, and core platform concepts
Data Processing and Transformations- PySpark DataFrame transformations
- User-defined functions (UDFs)
- Apache Spark SQL operations (joins, aggregations, filtering)
- Delta Lake fundamentals (tables, transactions, optimization)
Data Ingestion and ELT Development- Data ingestion using Spark SQL and PySpark
- Handling structured and semi-structured data
- ETL patterns and transformations
Productionizing Data Pipelines- Scheduling and monitoring jobs
- Databricks Workflows / Jobs orchestration
- Pipeline deployment and operationalization
Data Governance and Quality- Data access control and governance
- Unity Catalog basics
- Data quality concepts and management

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q31-Q36):

NEW QUESTION # 31
A data engineer needs to find all customers who have never placed an order. The customers table contains customer_id, customer_name, and other customer attributes. The orders table contains order_id, customer_id, and other order attributes. Both tables share customer_id as the join key. The result must include only customer columns, with no order-related columns in the output.
Which expression exactly achieves this requirement?

Answer: A


NEW QUESTION # 32
What is stored in a Databricks customer's cloud account?

Answer: C

Explanation:
In a Databricks customer's cloud account, the primary elements stored include:
Data: This is the central type of content stored in the customer's cloud account. Data might include various datasets, tables, and files that are used and managed through Databricks platforms.
Notebooks: These are also stored within a customer's cloud account. Notebooks include scripts, notes, and other information necessary for data analysis and processing tasks.
Cluster management metadata is indeed managed through the cloud, but it's primarily handled by Databricks rather than stored directly in the customer's account. The Databricks web application itself is not stored within the customer's cloud account; rather, it's a service provided by Databricks.
Reference:
Databricks documentation: Data in Databricks


NEW QUESTION # 33
A data engineer wants to schedule their Databricks SQL dashboard to refresh every hour, but they only want the associated SQL endpoint to be running when It is necessary. The dashboard has multiple queries on multiple datasets associated with it. The data that feeds the dashboard is automatically processed using a Databricks Job.
Which approach can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

Answer: D

Explanation:
To minimize the total running time of the SQL endpoint used in the refresh schedule of a dashboard in Databricks, the most effective approach is to utilize the Auto Stop feature. This feature allows the SQL endpoint to automatically stop after a period of inactivity, ensuring that it only runs when necessary, such as during the dashboard refresh or when actively queried. This minimizes resource usage and associated costs by ensuring the SQL endpoint is not running idle outside of these operations.
References:Databricks documentation on SQL endpoints: SQL Endpoints in Databricks


NEW QUESTION # 34
A data engineering team is building a new data transformation notebook. During development, they need fast testing, quick code changes, and easy debugging. Later, the notebook will run nightly as a scheduled job without human intervention. They want to optimize for development speed. Which compute should they use during development?

Answer: D

Explanation:
Interactive compute is designed for iterative notebook development, rapid code changes, and debugging. The completed notebook can later be moved to job compute for unattended nightly execution.


NEW QUESTION # 35
The Delta transaction log for the 'students' tables is shown using the 'DESCRIBE HISTORY students' command. A Data Engineer needs to query the table as it existed before the UPDATE operation listed in the log.

Which command should the Data Engineer use to achieve this? (Choose two.)

Answer: C,D


NEW QUESTION # 36
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