[Mar-2024] Verified Databricks Exam Dumps with Databricks-Certified-Data-Engineer-Associate Exam Study Guide [Q11-Q31]

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[Mar-2024] Verified Databricks Exam Dumps with Databricks-Certified-Data-Engineer-Associate Exam Study Guide

Best Quality Databricks Databricks-Certified-Data-Engineer-Associate Exam Questions PracticeMaterial Realistic Practice Exams [2024]

The GAQM Databricks-Certified-Data-Engineer-Associate exam is a comprehensive test of an individual’s knowledge of Databricks and its related technologies. It evaluates the ability of candidates to design, build, and maintain data pipelines using Databricks. Databricks Certified Data Engineer Associate Exam certification is ideal for data engineers, data architects, and data scientists who want to showcase their skills and knowledge in working with Databricks. Earning the certification can help individuals advance their careers and lead to better job opportunities and higher salaries.

The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Certification Exam is a rigorous exam that tests candidates on their practical skills and knowledge of data engineering. Candidates will be required to complete a series of multiple-choice questions and hands-on tasks that simulate real-world data engineering scenarios. Databricks-Certified-Data-Engineer-Associate exam is designed to ensure that candidates have the necessary skills and knowledge to build and maintain large-scale data pipelines.

NO.11 Which of the following tools is used by Auto Loader process data incrementally?

Checkpointing

Spark Structured Streaming

Data Explorer

Unity Catalog

Databricks SQL

NO.12 A data engineer has created a new database using the following command:
CREATE DATABASE IF NOT EXISTS customer360;
In which of the following locations will the customer360 database be located?

dbfs:/user/hive/database/customer360

dbfs:/user/hive/warehouse

dbfs:/user/hive/customer360

More information is needed to determine the correct response

NO.13 A data engineer needs to apply custom logic to identify employees with more than 5 years of experience in array column employees in table stores. The custom logic should create a new column exp_employees that is an array of all of the employees with more than 5 years of experience for each row. In order to apply this custom logic at scale, the data engineer wants to use the FILTER higher-order function.
Which of the following code blocks successfully completes this task?

Option A

Option B

Option C

Option D

Option E

NO.14 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 Development 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 once and the pipeline will shut down. The compute resources will be terminated.

All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist until the pipeline is shut down.

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

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

NO.15 A new data engineering team team. has been assigned to an ELT project. The new data engineering team will need full privileges on the database customers to fully manage the project.
Which of the following commands can be used to grant full permissions on the database to the new data engineering team?

GRANT USAGE ON DATABASE customers TO team;

GRANT ALL PRIVILEGES ON DATABASE team TO customers;

GRANT SELECT PRIVILEGES ON DATABASE customers TO teams;

GRANT SELECT CREATE MODIFY USAGE PRIVILEGES ON DATABASE customers TO team;

GRANT ALL PRIVILEGES ON DATABASE customers TO team;

NO.16 A data engineer wants to schedule their Databricks SQL dashboard to refresh every hour, but they only want the associated SQL endpoint to be running when it is necessary. The dashboard has multiple queries on multiple datasets associated with it. The data that feeds the dashboard is automatically processed using a Databricks Job.
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 turn on the Auto Stop feature for the SQL endpoint.

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

They can reduce the cluster size of the SQL endpoint.

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.

NO.17 Which of the following describes a benefit of creating an external table from Parquet rather than CSV when using a CREATE TABLE AS SELECT statement?

Parquet files can be partitioned

CREATE TABLE AS SELECT statements cannot be used on files

Parquet files have a well-defined schema

Parquet files have the ability to be optimized

Parquet files will become Delta tables

NO.18 Which of the following statements regarding the relationship between Silver tables and Bronze tables is always true?

Silver tables contain a less refined, less clean view of data than Bronze data.

Silver tables contain aggregates while Bronze data is unaggregated.

Silver tables contain more data than Bronze tables.

Silver tables contain a more refined and cleaner view of data than Bronze tables.

Silver tables contain less data than Bronze tables.

NO.19 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.

NO.20 An engineering manager uses a Databricks SQL query to monitor ingestion latency for each data source. The manager checks the results of the query every day, but they are manually rerunning the query each day and waiting for the results.
Which of the following approaches can the manager use to ensure the results of the query are updated each day?

They can schedule the query to refresh every 1 day from the SQL endpoint’s page in Databricks SQL.

They can schedule the query to refresh every 12 hours from the SQL endpoint’s page in Databricks SQL.

They can schedule the query to refresh every 1 day from the query’s page in Databricks SQL.

They can schedule the query to run every 1 day from the Jobs UI.

They can schedule the query to run every 12 hours from the Jobs UI.

NO.21 A data architect has determined that a table of the following format is necessary:

Which of the following code blocks uses SQL DDL commands to create an empty Delta table in the above format regardless of whether a table already exists with this name?

Option A

Option B

Option C

Option D

Option E

NO.22 A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to an ELT job. The ELT job has its Databricks SQL query that returns the number of input records containing unexpected NULL values. The data engineer wants their entire team to be notified via a messaging webhook whenever this value reaches 100.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of NULL values reaches 100?

They can set up an Alert with a custom template.

They can set up an Alert with a new email alert destination.

They can set up an Alert with a new webhook alert destination.

They can set up an Alert with one-time notifications.

They can set up an Alert without notifications.

NO.23 A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to an ELT job. The ELT job has its Databricks SQL query that returns the number of input records containing unexpected NULL values. The data engineer wants their entire team to be notified via a messaging webhook whenever this value reaches 100.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of NULL values reaches 100?

They can set up an Alert with a custom template.

They can set up an Alert with a new email alert destination.

They can set up an Alert with a new webhook alert destination.

They can set up an Alert with one-time notifications.

They can set up an Alert without notifications.

NO.24 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.

NO.25 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

NO.26 Which of the following describes the storage organization of a Delta table?

Delta tables are stored in a single file that contains data, history, metadata, and other attributes.

Delta tables store their data in a single file and all metadata in a collection of files in a separate location.

Delta tables are stored in a collection of files that contain data, history, metadata, and other attributes.

Delta tables are stored in a collection of files that contain only the data stored within the table.

Delta tables are stored in a single file that contains only the data stored within the table.

NO.27 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 Development 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 once and the pipeline will shut down. The compute resources will be terminated.

All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist until the pipeline is shut down.

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

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

NO.28 A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following commands could the data engineering team use to access sales in PySpark?

SELECT * FROM sales

There is no way to share data between PySpark and SQL.

spark.sql(“sales”)

spark.delta.table(“sales”)

spark.table(“sales”)

NO.29 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 cade block used by the data engineer is below:

If the data engineer only wants the query to execute a micro-batch to process data every 5 seconds, which of the following lines of code should the data engineer use to fill in the blank?

trigger(“5 seconds”)

trigger()

trigger(once=”5 seconds”)

trigger(processingTime=”5 seconds”)

trigger(continuous=”5 seconds”)

NO.30 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.

NO.31 Which of the following data workloads will utilize a Gold table as its source?

A job that enriches data by parsing its timestamps into a human-readable format

A job that aggregates uncleaned data to create standard summary statistics

A job that cleans data by removing malformatted records

A job that queries aggregated data designed to feed into a dashboard

A job that ingests raw data from a streaming source into the Lakehouse

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