[2023] Practice with these Databricks-Certified-Data-Engineer-Associate dumps Certification Sample Questions [Q15-Q35]

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[2023] Practice with these Databricks-Certified-Data-Engineer-Associate dumps Certification Sample Questions

Get Instant Access of 100% REAL Databricks-Certified-Data-Engineer-Associate DUMP Pass Your Exam Easily

The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) certification exam is an excellent opportunity for data professionals to validate their skills in designing, building, and maintaining data pipelines using Databricks. Databricks Certified Data Engineer Associate Exam certification exam covers a wide range of topics and is designed to test the candidate’s knowledge of data engineering fundamentals, Databricks architecture, data modeling, and data processing. Passing the certification exam provides an individual with a globally recognized certification that can enhance their career prospects in the data engineering field.

The Databricks Databricks-Certified-Data-Engineer-Associate exam consists of 60 multiple-choice questions and is designed to test your understanding of Databricks concepts, including data engineering, data processing, data storage, and data analysis. To pass the exam, you must score at least 70%. Databricks-Certified-Data-Engineer-Associate exam can be taken online and is available in several languages, including English, Spanish, and Chinese. Upon passing the exam, you will receive a Databricks Certified Data Engineer Associate certification, which is recognized globally as a mark of expertise in big data processing using Databricks.

Q15. Which of the following commands can be used to write data into a Delta table while avoiding the writing of duplicate records?

DROP

IGNORE

MERGE

APPEND

INSERT

Q16. A data engineer has realized that they made a mistake when making a daily update to a table. They need to use Delta time travel to restore the table to a version that is 3 days old. However, when the data engineer attempts to time travel to the older version, they are unable to restore the data because the data files have been deleted.
Which of the following explains why the data files are no longer present?

The VACUUM command was run on the table

The TIME TRAVEL command was run on the table

The DELETE HISTORY command was run on the table

The OPTIMIZE command was nun on the table

The HISTORY command was run on the table

Q17. A data engineer has a Job with multiple tasks that runs nightly. Each of the tasks runs slowly because the clusters take a long time to start.
Which of the following actions can the data engineer perform to improve the start up time for the clusters used for the Job?

They can use endpoints available in Databricks SQL

They can use jobs clusters instead of all-purpose clusters

They can configure the clusters to be single-node

They can use clusters that are from a cluster pool

They can configure the clusters to autoscale for larger data sizes

Q18. A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).
Which of the following code blocks creates this SQL UDF?

Q19. Which of the following tools is used by Auto Loader process data incrementally?

Checkpointing

Spark Structured Streaming

Data Explorer

Unity Catalog

Databricks SQL

Q20. A data engineer is designing a data pipeline. The source system generates files in a shared directory that is also used by other processes. As a result, the files should be kept as is and will accumulate in the directory. The data engineer needs to identify which files are new since the previous run in the pipeline, and set up the pipeline to only ingest those new files with each run.
Which of the following tools can the data engineer use to solve this problem?

Unity Catalog

Delta Lake

Databricks SQL

Data Explorer

Auto Loader

Q21. A data engineer wants to create a data entity from a couple of tables. The data entity must be used by other data engineers in other sessions. It also must be saved to a physical location.
Which of the following data entities should the data engineer create?

Database

Function

View

Temporary view

Table

Q22. Which of the following describes the relationship between Bronze tables and raw data?

Bronze tables contain less data than raw data files.

Bronze tables contain more truthful data than raw data.

Bronze tables contain aggregates while raw data is unaggregated.

Bronze tables contain a less refined view of data than raw data.

Bronze tables contain raw data with a schema applied.

Q23. Which of the following commands will return the location of database customer360?

DESCRIBE LOCATION customer360;

DROP DATABASE customer360;

DESCRIBE DATABASE customer360;

ALTER DATABASE customer360 SET DBPROPERTIES (‘location’ = ‘/user’};

USE DATABASE customer360;

Q24. A data engineer wants to schedule their Databricks SQL dashboard to refresh once per day, but they only want the associated SQL endpoint to be running when it is necessary.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

They can ensure the dashboard’s SQL endpoint matches each of the queries’ SQL endpoints.

They can set up the dashboard’s SQL endpoint to be serverless.

They can turn on the Auto Stop feature for the SQL endpoint.

They can reduce the cluster size of the SQL endpoint.

They can ensure the dashboard’s SQL endpoint is not one of the included query’s SQL endpoint.

Q25. 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?

GRANT VIEW ON CATALOG customers TO team;

GRANT CREATE ON DATABASE customers TO team;

GRANT USAGE ON CATALOG team TO customers;

GRANT CREATE ON DATABASE team TO customers;

GRANT USAGE ON DATABASE customers TO team;

Q26. Which of the following benefits is provided by the array functions from Spark SQL?

An ability to work with data in a variety of types at once

An ability to work with data within certain partitions and windows

An ability to work with time-related data in specified intervals

An ability to work with complex, nested data ingested from JSON files

An ability to work with an array of tables for procedural automation

Q27. A data engineer has a single-task Job that runs each morning before they begin working. After identifying an upstream data issue, they need to set up another task to run a new notebook prior to the original task.
Which of the following approaches can the data engineer use to set up the new task?

They can clone the existing task in the existing Job and update it to run the new notebook.

They can create a new task in the existing Job and then add it as a dependency of the original task.

They can create a new task in the existing Job and then add the original task as a dependency of the new task.

They can create a new job from scratch and add both tasks to run concurrently.

They can clone the existing task to a new Job and then edit it to run the new notebook.

Q28. 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?

The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.

The names of the files to be copied were not included with the FILES keyword.

The previous day’s file has already been copied into the table.

The PARQUET file format does not support COPY INTO.

The COPY INTO statement requires the table to be refreshed to view the copied rows.

Q29. A Delta Live Table pipeline includes two datasets defined using STREAMING LIVE TABLE. Three datasets are defined against Delta Lake table sources using LIVE TABLE.
The table is configured to run in Production mode using the Continuous Pipeline Mode.
Assuming previously unprocessed data exists and all definitions are valid, what is the expected outcome after clicking Start to update the pipeline?

All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist to allow for additional testing.

All datasets will be updated once and the pipeline will persist without any processing. The compute resources will persist but go unused.

All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will be deployed for the update and terminated when the pipeline is stopped.

All datasets will be updated once and the pipeline will shut down. The compute resources will be terminated.

All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing.

Q30. Which of the following describes a scenario in which a data team will want to utilize cluster pools?

An automated report needs to be refreshed as quickly as possible.

An automated report needs to be made reproducible.

An automated report needs to be tested to identify errors.

An automated report needs to be version-controlled across multiple collaborators.

An automated report needs to be runnable by all stakeholders.

Q31. Which of the following Git operations must be performed outside of Databricks Repos?

Commit

Pull

Push

Clone

Merge

Q32. A dataset has been defined using Delta Live Tables and includes an expectations clause:
CONSTRAINT valid_timestamp EXPECT (timestamp > ‘2020-01-01’) ON VIOLATION DROP ROW What is the expected behavior when a batch of data containing data that violates these constraints is processed?

Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table.

Records that violate the expectation are added to the target dataset and flagged as invalid in a field added to the target dataset.

Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log.

Records that violate the expectation are added to the target dataset and recorded as invalid in the event log.

Records that violate the expectation cause the job to fail.

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