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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 146

A data engineer has a Python notebook in Databricks, but they need to use SQL to accomplish a specific task within a cell. They still want all of the other cells to use Python without making any changes to those cells.
Which of the following describes how the data engineer can use SQL within a cell of their Python notebook?

Correct Answer: B
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Question 147

A pipeline uses COPY INTO to ingest CSV files from cloud object storage into a Unity Catalog Delta table. Some files are occasionally re-uploaded with corrections using the same filename.
The engineer needs the corrected data to be ingested as soon as it becomes available.
What should the engineer do?

Correct Answer: B
COPY INTO is idempotent by default and tracks files that have already been loaded into the target table. A corrected file uploaded under the same name and path can therefore be treated as previously processed and skipped. The reliable pattern is to publish the correction under a new unique filename so that ingestion detects it as a new file. The pipeline can then use a business key with MERGE, UPDATE, or equivalent transformation logic to apply the corrected values to the target Delta table. Overwriting or recreating the complete table risks unnecessary data loss, increases processing cost, and disrupts downstream consumers. Reloading every historical source file is also inefficient and can introduce duplicates. Therefore, option B supports incremental ingestion while applying corrections safely and efficiently.
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Question 148

A data engineer is designing an ETL pipeline to process both streaming and batch data from multiple sources The pipeline must ensure data quality, handle schema evolution, and provide easy maintenance. The team is considering using Delta Live Tables (DLT) in Databricks to achieve these goals. They want to understand the key features and benefits of DLT that make it suitable for this use case.
Why is Delta Live Tables (DLT) an appropriate choice?

Correct Answer: A
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Question 149

Which file format is used for storing Delta Lake Table?

Correct Answer: A
Delta Lake tables use the Parquet format as their underlying storage format. Delta Lake enhances Parquet by adding a transaction log that keeps track of all the operations performed on the table. This allows features like ACID transactions, scalable metadata handling, and schema enforcement, making it an ideal choice for big data processing and management in environments like Databricks.
References:Databricks documentation on Delta Lake: Delta Lake Overview
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Question 150

A data engineer runs a statement every day to copy the previous day's sales into the table transactions. Each day's sales are in their own file in the location "/transactions/raw".
Today, the data engineer runs the following command to complete this task:

After running the command today, the data engineer notices that the number of records in table transactions has not changed.
Which of the following describes why the statement might not have copied any new records into the table?

Correct Answer: C
The COPY INTO statement is an idempotent operation, which means that it will skip any files that have already been loaded into the target table1. This ensures that the data is not duplicated or corrupted by multiple attempts to load the same file. Therefore, if the data engineer runs the same command every day without specifying the names of the files to be copied with the FILES keyword or a glob pattern with the PATTERN keyword, the statement will only copy the first file that matches the source location and ignore the rest. To avoid this problem, the data engineer should either use the FILES or PATTERN keywords to filter the files to be copied based on the date or some other criteria, or delete the files from the source location after they are copied into the table2. Reference: 1: COPY INTO | Databricks on AWS 2: Get started using COPY INTO to load data | Databricks on AWS
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