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  1. Home
  2. GAQM Certification
  3. Databricks-Certified-Data-Engineer-Associate Exam
  4. GAQM.Databricks-Certified-Data-Engineer-Associate.v2026-07-23.q248 Dumps
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Question 111

A data engineer needs to use a Delta table as part of a data pipeline, but they do not know if they have the appropriate permissions.
In which of the following locations can the data engineer review their permissions on the table?

Correct Answer: E
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Question 112

A data engineer uploads a CSV file using the Create or modify a table using file upload option in Databricks. To avoid incorrect schema inference, the engineer disables Automatically detect column types before creating a Unity Catalog-managed table.
What is the outcome?

Correct Answer: A
When Automatically detect column types is disabled during file upload, Databricks does not infer specialized data types from the CSV values. Instead, every uploaded column is created as STRING. This behavior prevents values that resemble numbers, dates, or Boolean values from being automatically assigned potentially incorrect types. The engineer can subsequently transform or cast individual columns into the required target types as part of a controlled Silver-layer process. Option B is incorrect because partial numeric inference does not occur when automatic detection is disabled. Option C is incorrect because Databricks can create the table without manually supplied types by using STRING for every column. Option D is also incorrect because disabling detection determines the schema behavior for the table creation operation. Therefore, option A accurately describes the result.
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Question 113

A data engineer has three tables in a Delta Live Tables (DLT) pipeline. They have configured the pipeline to drop invalid records at each table. They notice that some data is being dropped due to quality concerns at some point in the DLT pipeline. They would like to determine at which table in their pipeline the data is being dropped.
Which of the following approaches can the data engineer take to identify the table that is dropping the records?

Correct Answer: D
One of the features of DLT is that it provides data quality metrics for each dataset in the pipeline, such as the number of records that pass or fail expectations, the number of records that are dropped, and the number of records that are written to the target. These metrics can be accessed from the DLT pipeline page, where the data engineer can click on each table and view the data quality statistics for the latest update or any previous update. This way, they can identify which table is dropping the records and why. References:
* Monitor Delta Live Tables pipelines
* Manage data quality with Delta Live Tables
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Question 114

A data engineer that is new to using Python needs to create a Python function to add two integers together and return the sum?
Which of the following code blocks can the data engineer use to complete this task?

Correct Answer: D
https://www.w3schools.com/python/python_functions.asp
https://www.geeksforgeeks.org/python-functions/
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Question 115

A data engineer has written a function in a Databricks Notebook to calculate the population of bacteria in a given medium.

Analysts use this function in the notebook and sometimes provide input arguments of the wrong data type, which can cause errors during execution.
Which Databricks feature will help the data engineer quickly identify if an incorrect data type has been provided as input?

Correct Answer: B
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