[Jun 16, 2023] Verified Databricks-Certified-Professional-Data-Engineer dumps and 220 unique questions [Q11-Q30]

Rate this post

[Jun 16, 2023] Verified Databricks-Certified-Professional-Data-Engineer dumps and 220 unique questions

Databricks-Certified-Professional-Data-Engineer Dumps for Pass Guaranteed – Pass Databricks-Certified-Professional-Data-Engineer Exam 2023

The Databricks Certified Professional Data Engineer certification exam is designed for professionals who want to prove their expertise in designing, building, and maintaining data processing systems using Databricks. Databricks is a cloud-based data platform that provides a unified analytics engine for data processing, machine learning, and visualization. This certification exam tests the candidate’s knowledge and skills in various areas, including data engineering, data processing, data modeling, and data architecture.

Q11. An engineering manager uses a Databricks SQL query to monitor their team’s progress on fixes related to
customer-reported bugs. 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 up-dated each
day?

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

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 run every 1 day from the Jobs UI

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

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

Q12. A denote the event ‘student is female’ and let B denote the event ‘student is French’. In a class of 100 students
suppose 60 are French, and suppose that 10 of the French students are females. Find the probability that if I
pick a French student, it will be a girl, that is, find P(A|B).

1/3

2/3

1/6

2/6

Q13. You are currently asked to work on building a data pipeline, you have noticed that you are currently working on a very large scale ETL many data dependencies, which of the following tools can be used to address this problem?

AUTO LOADER

JOBS and TASKS

SQL Endpoints

DELTA LIVE TABLES

STRUCTURED STREAMING with MULTI HOP

Q14. Which of the following data workloads will utilize a Bronze table as its source?

A job that queries aggregated data to publish key insights into a dashboard

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

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

A job that develops a feature set for a machine learning application

A job that aggregates cleaned data to create standard summary statistics

Q15. A data architect is designing a data model that works for both video-based machine learning work-loads and
highly audited batch ETL/ELT workloads.
Which of the following describes how using a data lakehouse can help the data architect meet the needs of
both workloads?

A data lakehouse requires very little data modeling

A data lakehouse combines compute and storage for simple governance

A data lakehouse fully exists in the cloud

A data lakehouse stores unstructured data and is ACID-compliant

A data lakehouse provides autoscaling for compute clusters

Q16. You are asked to setup two tasks in a databricks job, the first task runs a notebook to download the data from a remote system, and the second task is a DLT pipeline that can process this data, how do you plan to configure this in Jobs UI

Single job cannot have a notebook task and DLT Pipeline task, use two different jobs with linear dependency.

Jobs UI does not support DTL pipeline, setup the first task using jobs UI and setup the DLT to run in continuous mode.

Jobs UI does not support DTL pipeline, setup the first task using jobs UI and setup the DLT to run in trigger mode.

Single job can be used to setup both notebook and DLT pipeline, use two different tasks with linear dependency.

Add first step in the DLT pipeline and run the DLT pipeline as triggered mode in JOBS UI

Q17. A newly joined team member John Smith in the Marketing team currently has access read access to sales tables but does not have access to update the table, which of the following commands help you accomplish this?

GRANT UPDATE ON TABLE table_name TO [email protected]

GRANT USAGE ON TABLE table_name TO [email protected]

GRANT MODIFY ON TABLE table_name TO [email protected]

GRANT UPDATE TO TABLE table_name ON [email protected]

GRANT MODIFY TO TABLE table_name ON [email protected]

Q18. What is the purpose of the silver layer in a Multi hop architecture?

Replaces a traditional data lake

Efficient storage and querying of full, unprocessed history of data

Eliminates duplicate data, quarantines bad data

Refined views with aggregated data

Optimized query performance for business-critical data

Q19. A data engineer has set up two Jobs that each run nightly. The first Job starts at 12:00 AM, and it usually
completes in about 20 minutes. The second Job depends on the first Job, and it starts at 12:30 AM. Sometimes,
the second Job fails when the first Job does not complete by 12:30 AM.
Which of the following approaches can the data engineer use to avoid this problem?

They can set up a retry policy on the first Job to help it run more quickly

They can use cluster pools to help the Jobs run more efficiently

They can limit the size of the output in the second Job so that it will not fail as easily

They can set up the data to stream from the first Job to the second Job

They can utilize multiple tasks in a single job with a linear dependency

Q20. The team has decided to take advantage of table properties to identify a business owner for each table, which of the following table DDL syntax allows you to populate a table property identifying the business owner of a table CREATE TABLE inventory (id INT, units FLOAT)

SET TBLPROPERTIES business_owner = ‘supply chain’
CREATE TABLE inventory (id INT, units FLOAT)

TBLPROPERTIES (business_owner = ‘supply chain’)

CREATE TABLE inventory (id INT, units FLOAT)
SET (business_owner = ‘supply chain’)

CREATE TABLE inventory (id INT, units FLOAT)
SET PROPERTY (business_owner = ‘supply chain’)

CREATE TABLE inventory (id INT, units FLOAT)
SET TAG (business_owner = ‘supply chain’)

Q21. You are working on a process to query the table based on batch date, and batch date is an input parameter and expected to change every time the program runs, what is the best way to we can parameterize the query to run without manually changing the batch date?

Create a notebook parameter for batch date and assign the value to a python variable and use a spark data frame to filter the data based on the python variable

Create a dynamic view that can calculate the batch date automatically and use the view to query the data

There is no way we can combine python variable and spark code

Manually edit code every time to change the batch date

Store the batch date in the spark configuration and use a spark data frame to filter the data based on the spark configuration.

Q22. How do you create a delta live tables pipeline and deploy using DLT UI?

Within the Workspace UI, click on Workflows, select Delta Live tables and create a pipeline and select the notebook with DLT code.

Under Cluster UI, select SPARK UI and select Structured Streaming and click create pipeline and select the notebook with DLT code.

There is no UI, you can only setup DELTA LIVE TABLES using Python and SQL API and select the notebook with DLT code.

Use VS Code and download DBX plugin, once the plugin is loaded you can build DLT pipelines and select the notebook with DLT code.

Within the Workspace UI, click on SQL Endpoint, select Delta Live tables and create pipelinea and select the notebook with DLT code.

Q23. 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

Auto Loader

Data Explorer

Delta Lake

Databricks SQL

Q24. Data engineering team has a job currently setup to run a task load data into a reporting table every day at 8: 00 AM takes about 20 mins, Operations teams are planning to use that data to run a second job, so they access latest complete set of data. What is the best to way to orchestrate this job setup?

Add Operation reporting task in the same job and set the Data Engineering task to de-pend on Operations reporting task

Setup a second job to run at 8:20 AM in the same workspace

Add Operation reporting task in the same job and set the operations reporting task to depend on Data Engineering task

Use Auto Loader to run every 20 mins to read the initial table and set the trigger to once and create a second job

Setup a Delta live to table based on the first table, set the job to run in continuous mode

Q25. Which of the following scenarios is the best fit for AUTO LOADER?

Efficiently process new data incrementally from cloud object storage

Efficiently move data incrementally from one delta table to another delta table

Incrementally process new data from streaming data sources like Kafka into delta lake

Incrementally process new data from relational databases like MySQL

Efficiently copy data from one data lake location to another data lake location

Q26. Which of the following command can be used to drop a managed delta table and the underlying files in the storage?

DROP TABLE table_name CASCADE

DROP TABLE table_name

Use DROP TABLE table_name command and manually delete files using com-mand dbutils.fs.rm(“/path”,True)

DROP TABLE table_name INCLUDE_FILES

DROP TABLE table and run VACUUM command

Q27. You are tasked to set up a set notebook as a job for six departments and each department can run the task parallelly, the notebook takes an input parameter dept number to process the data by department, how do you go about to setup this up in job?

Use a single notebook as task in the job and use dbutils.notebook.run to run each note-book with parameter in a different cell

A task in the job cannot take an input parameter, create six notebooks with hardcoded dept number and setup six tasks with linear dependency in the job

A task accepts key-value pair parameters, creates six tasks pass department number as parameter foreach task with no dependency in the job as they can all run in parallel.
(Correct)

A parameter can only be passed at the job level, create six jobs pass department number to each job with linear job dependency

A parameter can only be passed at the job level, create six jobs pass department number to each job with no job dependency

Q28. The current ELT pipeline is receiving data from the operations team once a day so you had setup an AUTO LOADER process to run once a day using trigger (Once = True) and scheduled a job to run once a day, operations team recently rolled out a new feature that allows them to send data every 1 min, what changes do you need to make to AUTO LOADER to process the data every 1 min.

Convert AUTO LOADER to structured streaming

Change AUTO LOADER trigger to .trigger(ProcessingTime = “1 minute”)

Setup a job cluster run the notebook once a minute

Enable stream processing

Change AUTO LOADER trigger to (“1 minute”)

Q29. You were asked to write python code to stop all running streams, which of the following command can be used to get a list of all active streams currently running so we can stop them, fill in the blank.
1.for s in _______________:
2. s.stop()

Spark.getActiveStreams()

spark.streams.active

activeStreams()

getActiveStreams()

spark.streams.getActive

Q30. Below sample input data contains two columns, one cartId also known as session id, and the second column is called items, every time a customer makes a change to the cart this is stored as an array in the table, the Marketing team asked you to create a unique list of item’s that were ever added to the cart by each customer, fill in blanks by choosing the appropriate array function so the query produces below expected result as shown below.
Schema: cartId INT, items Array<INT>
Sample Data

1.SELECT cartId, ___ (___(items)) as items
2.FROM carts GROUP BY cartId
Expected result:
cartId items
1 [1,100,200,300,250]

FLATTEN, COLLECT_UNION

ARRAY_UNION, FLATTEN

ARRAY_UNION, ARRAY_DISTINT

ARRAY_UNION, COLLECT_SET

ARRAY_DISTINCT, ARRAY_UNION

By earning the Databricks Certified Professional Data Engineer certification, data professionals can demonstrate their expertise in using the Databricks platform to build and manage data solutions. This certification can help individuals advance their careers, as well as provide organizations with a way to identify and hire qualified data professionals who can help them achieve their data-driven goals.

Latest 100% Passing Guarantee – Brilliant Databricks-Certified-Professional-Data-Engineer Exam Questions PDF: https://www.free4dump.com/Databricks-Certified-Professional-Data-Engineer-braindumps-torrent.html