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Pass Guaranteed Quiz Databricks - Databricks-Certified-Data-Engineer-Associate–Professional Valid Test Answers

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q19-Q24):

NEW QUESTION # 19
A data organization leader is upset about the data analysis team's reports being different from the data engineering team's reports. The leader believes the siloed nature of their organization's data engineering and data analysis architectures is to blame.
Which of the following describes how a data lakehouse could alleviate this issue?

A. Both teams would use the same source of truth for their work
B. Both teams would be able to collaborate on projects in real-time
C. Both teams would reorganize to report to the same department
D. Both teams would respond more quickly to ad-hoc requests
E. Both teams would autoscale their work as data size evolves

Answer: A

Explanation:
A data lakehouse is a data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data12. By using a data lakehouse, both the data analysis and data engineering teams can access the same data sources and formats, ensuring data consistency and quality across their reports. A data lakehouse also supports schema enforcement and evolution, data validation, and time travel to old table versions, which can help resolve data conflicts and errors1. References: 1: What is a Data Lakehouse? - Databricks 2: What is a data lakehouse? | IBM

NEW QUESTION # 20
Which of the following commands will return the number of null values in the member_id column?

A. SELECT count(member_id) FROM my_table;
B. SELECT null(member_id) FROM my_table;
C. SELECT count_null(member_id) FROM my_table;
D. SELECT count(member_id) - count_null(member_id) FROM my_table;
E. SELECT count_if(member_id IS NULL) FROM my_table;

Answer: E

Explanation:
Explanation
https://docs.databricks.com/en/sql/language-manual/functions/count.html Returns A BIGINT.
If * is specified also counts row containing NULL values.
If expr are specified counts only rows for which all expr are not NULL.
If DISTINCT duplicate rows are not counted.

NEW QUESTION # 21
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.
The code block used by the data engineer is below:

If the data engineer only wants the query to process all of the available data in as many batches as required, which of the following lines of code should the data engineer use to fill in the blank?

A. processingTime(1)
B. trigger(continuous="once")
C. trigger(parallelBatch=True)
D. trigger(availableNow=True)
E. trigger(processingTime="once")

Answer: D

Explanation:
https://spark.apache.org/docs/latest/api/python/reference/pyspark.ss/api/pyspark.sql.streaming.DataStreamWriter.trigger.html

NEW QUESTION # 22
Which of the following describes the relationship between Bronze tables and raw data?

A. Bronze tables contain more truthful data than raw data.
B. Bronze tables contain a less refined view of data than raw data.
C. Bronze tables contain less data than raw data files.
D. Bronze tables contain aggregates while raw data is unaggregated.
E. Bronze tables contain raw data with a schema applied.

Answer: E

Explanation:
Bronze tables are the first layer of a medallion architecture, which is a data design pattern used to organize data in a lakehouse. Bronze tables contain raw data ingested from various sources, such as RDBMS data, JSON files, IoT data, etc. The table structures in this layer correspond to the source system table structures
"as-is", along with any additional metadata columns that capture the load date/time, process ID, etc. The only transformation applied to the raw data in this layer is to apply a schema, which defines the column names and data types of the table. The schema can be inferred from the data source or specified explicitly. Applying a schema to the raw data enables the use of SQL and other structured query languages to access and analyze the data. Therefore, option E is the correct answer. References: What is a Medallion Architecture?, Raw Data Ingestion into Delta Lake Bronze tables using Azure Synapse Mapping Data Flow, Apache Spark + Delta Lake concepts, Delta Lake Architecture & Azure Databricks Workspace.

NEW QUESTION # 23
A new data engineering team has been assigned to work on a project. The team will need access to database customers in order to see what tables already exist. The team has its own group team.
Which of the following commands can be used to grant the necessary permission on the entire database to the new team?

A. GRANT CREATE ON DATABASE customers TO team;
B. GRANT USAGE ON CATALOG team TO customers;
C. GRANT VIEW ON CATALOG customers TO team;
D. GRANT USAGE ON DATABASE customers TO team;

Answer: D

NEW QUESTION # 24
......

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