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

SectionWeightObjectives
Spark SQL and DataFrames15-20%- Write and execute Spark SQL queries
- Join and union DataFrames
- Aggregate and group data
- Handle null values and data quality
Lakehouse Platform Concepts10-15%- Explain data governance and security concepts
- Understand the Lakehouse architecture and its benefits
- Describe key Databricks Lakehouse platform components
Python for Data Engineering10-15%- Work with Spark APIs in Python
- Use PySpark for data processing
- Implement user-defined functions (UDFs)
Delta Lake Fundamentals20-25%- Explain Delta Lake features and benefits
- Create and manage Delta tables
- Write to and read from Delta tables
- Understand ACID transactions and time travel
Data Pipeline Architecture15-20%- Implement incremental data processing
- Understand ELT vs ETL patterns
- Monitor and optimize pipeline performance
- Design data pipelines for batch and streaming
Apache Spark Data Processing Fundamentals20-25%- Apply transformations and actions on DataFrames
- Create and use Spark DataFrames
- Work with structured data types (arrays, maps, structs)
- Use Spark SQL for data processing

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q232-Q237):

NEW QUESTION # 232
An engineering manager wants to monitor the performance of a recent project using a Databricks SQL query.
For the first week following the project's release, the manager wants the query results to be updated every minute. However, the manager is concerned that the compute resources used for the query will be left running and cost the organization a lot of money beyond the first week of the project's release.
Which of the following approaches can the engineering team use to ensure the query does not cost the organization any money beyond the first week of the project's release?

Answer: D

Explanation:
Explanation
If a dashboard is configured for automatic updates, it has a Scheduled button at the top, rather than a Schedule button. To stop automatically updating the dashboard and remove its subscriptions:
Click Scheduled.
In the Refresh every drop-down, select Never.
Click Save. The Scheduled button label changes to Schedule.
Source:https://learn.microsoft.com/en-us/azure/databricks/sql/user/dashboards/


NEW QUESTION # 233
A departing platform owner currently holds ownership of multiple catalogs and controls storage credentials and external locations. The data engineer wants to ensure continuity: transfer catalog ownership to the platform team group, delegate ongoing privilege management, and retain the ability to receive and share data via Delta Sharing.
Which role must be in place to perform these actions across the metastore?

Answer: B


NEW QUESTION # 234
A data engineer needs to create a table in Databricks using data from their organization's existing SQLite database.
They run the following command:

Which of the following lines of code fills in the above blank to successfully complete the task?

Answer: B

Explanation:
CREATE TABLE new_employees_table
USING JDBC
OPTIONS (
url "<jdbc_url>",
dbtable "<table_name>",
user '<username>',
password '<password>'
) AS
SELECT * FROM employees_table_vw
https://docs.databricks.com/external-data/jdbc.html#language-sql


NEW QUESTION # 235
Which of the following describes a benefit of creating an external table from Parquet rather than CSV when using a CREATE TABLE AS SELECT statement?

Answer: D

Explanation:
Option C is the correct answer because Parquet files have a well-defined schema that is embedded within the data itself. This means that the data types and column names of the Parquet files are automatically detected and preserved when creating an external table from them. This also enables the use of SQL and other structured query languages to access and analyze the data. CSV files, on the other hand, do not have a schema embedded in them, and require specifying the schema explicitly or inferring it from the data when creating an external table from them. This can lead to errors or inconsistencies in the data types and column names, and also increase the processing time and complexity.


NEW QUESTION # 236
A data engineer uses the Databricks workspace UI with Unity Catalog enabled. In Catalog Explorer, they select catalog corp_marketing, then schema campaigns, and see table email_stats. The engineer must let the growth-analysts group read email_stats from its SQL warehouses, but not create, alter, or delete any objects in corp_marketing or campaigns.
Which action sequence meets the requirement?

Answer: A


NEW QUESTION # 237
......

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