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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 181

Which of the following describes the storage organization of a Delta table?

Correct Answer: C
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Question 182


Calculate the total sales amount for each region and store the results in a new dataframe called region_sales.
Given the expected result:

Which code will generate the expected result?

Correct Answer: D
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Question 183

A data engineer team has decided to implement a new data platform on Databricks and is currently deciding how to store each kind of data on each data layer. What is the appropriate layer and data pairing for medallion architecture?

Correct Answer: C
In the Medallion architecture, the Silver layer holds cleansed and conformed data (such as master customer data), which has been cleaned, validated, and standardized after ingestion from the Bronze layer.
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Question 184

A data engineer needs to provide access to a group named manufacturing-team. The team needs privileges to create tables in the quality schema. Which set of SQL commands will grant a group named manufacturing-team to create tables in a schema named production with the parent catalog named manufacturing with the least privileges?

Correct Answer: A
To allow a group to create tables in a schema with least privileges, they need:
- GRANT CREATE TABLE on the schema
- GRANT USE SCHEMA on the schema
- GRANT USE CATALOG on the parent catalog
This ensures proper access without granting unnecessary privileges like creating schemas or catalogs.
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Question 185

Which query is performing a streaming hop from raw data to a Bronze table?

Correct Answer: D
The query performing a streaming hop from raw data to a Bronze table is identified by using the Spark streaming read capability and then writing to a Bronze table. Let's analyze the options:
* Option A: Utilizes .writeStream but performs a complete aggregation which is more characteristic of a roll-up into a summarized table rather than a hop into a Bronze table.
* Option B: Also uses .writeStream but calculates an average, which again does not typically represent the raw to Bronze transformation, which usually involves minimal transformations.
* Option C: This uses a basic .write with .mode("append") which is not a streaming operation, and hence not suitable for real-time streaming data transformation to a Bronze table.
* Option D: It employs spark.readStream.load() to ingest raw data as a stream and then writes it out with .writeStream, which is a typical pattern for streaming data into a Bronze table where raw data is captured in real-time and minimal transformation is applied. This approach aligns with the concept of a Bronze table in a modern data architecture, where raw data is ingested continuously and stored in a more accessible format.
References:Databricks documentation on Structured Streaming: Structured Streaming in Databricks
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