Get Prepared for Your Databricks-Certified-Data-Engineer-Associate Exam With Actual 47 Questions
Valid Databricks-Certified-Data-Engineer-Associate Test Answers Full-length Practice Certification Exams
Databricks Certified Data Engineer Associate Exam covers a wide range of topics, including data engineering fundamentals, data ingestion and processing, data warehousing and data lakes, data transformation and manipulation, and data quality and governance. Databricks-Certified-Data-Engineer-Associate exam is designed to provide a comprehensive understanding of Databricks and its features, and to ensure that candidates are equipped with the necessary skills to work with Databricks effectively.
NEW QUESTION # 15
In order for Structured Streaming to reliably track the exact progress of the processing so that it can handle any kind of failure by restarting and/or reprocessing, which of the following two approaches is used by Spark to record the offset range of the data being processed in each trigger?
- A. Structured Streaming cannot record the offset range of the data being processed in each trigger.
- B. Checkpointing and Write-ahead Logs
- C. Checkpointing and Idempotent Sinks
- D. Replayable Sources and Idempotent Sinks
- E. Write-ahead Logs and Idempotent Sinks
Answer: C
NEW QUESTION # 16
A data engineer wants to create a new table containing the names of customers that live in France.
They have written the following command:
A senior data engineer mentions that it is organization policy to include a table property indicating that the new table includes personally identifiable information (PII).
Which of the following lines of code fills in the above blank to successfully complete the task?
- A. "COMMENT PII"
- B. COMMENT "Contains PII"
- C. There is no way to indicate whether a table contains PII.
- D. PII
- E. TBLPROPERTIES PII
Answer: E
NEW QUESTION # 17
Which of the following Git operations must be performed outside of Databricks Repos?
- A. Clone
- B. Pull
- C. Merge
- D. Commit
- E. Push
Answer: A
NEW QUESTION # 18
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?
- A. spark.sql("sales")
- B. SELECT * FROM sales
- C. There is no way to share data between PySpark and SQL.
- D. spark.delta.table("sales")
- E. spark.table("sales")
Answer: D
NEW QUESTION # 19
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 USAGE ON CATALOG team TO customers;
- B. GRANT CREATE ON DATABASE customers TO team;
- C. GRANT USAGE ON DATABASE customers TO team;
- D. GRANT CREATE ON DATABASE team TO customers;
- E. GRANT VIEW ON CATALOG customers TO team;
Answer: C
NEW QUESTION # 20
Which of the following Structured Streaming queries is performing a hop from a Silver table to a Gold table?
- A.
- B.
- C.
- D.
- E.
Answer: B
NEW QUESTION # 21
An engineering manager wants to monitor the performance of a recent project using a Databricks SQL query.
For the first week following the project's release, the managerwants the query results to be updated every minute. However, the manager is concerned that the compute resources used for the query will be left running and cost the organization a lot of money beyond the first week of the project's release.
Which of the following approaches can the engineering team use to ensure the query does not cost the organization any money beyond the first week of the project's release?
- A. They can set the query's refresh schedule to end on a certain date in the query scheduler.
- B. They can set a limit to the number of DBUs that are consumed by the SQL Endpoint.
- C. They can set a limit to the number of individuals that are able to manage the query's refresh schedule.
- D. They can set the query's refresh schedule to end after a certain number of refreshes.
- E. They cannot ensure the query does not cost the organization money beyond the first week of the project's release.
Answer: A
NEW QUESTION # 22
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?
- A. GRANT SELECT CREATE MODIFY USAGE PRIVILEGES ON DATABASE customers TO team;
- B. GRANT USAGE ON DATABASE customers TO team;
- C. GRANT SELECT PRIVILEGES ON DATABASE customers TO teams;
- D. GRANT ALL PRIVILEGES ON DATABASE customers TO team;
- E. GRANT ALL PRIVILEGES ON DATABASE team TO customers;
Answer: D
NEW QUESTION # 23
A data engineer has three tables in a Delta Live Tables (DLT) pipeline. They have configured the pipeline to drop invalid records at each table. They notice that some data is being dropped due to quality concerns at some point in the DLT pipeline. They would like to determine at which table in their pipeline the data is being dropped.
Which of the following approaches can the data engineer take to identify the table that is dropping the records?
- A. They can navigate to the DLT pipeline page, click on each table, and view the data quality statistics.
- B. They can set up DLT to notify them via email when records are dropped.
- C. They can navigate to the DLT pipeline page, click on the "Error" button, and review the present errors.
- D. They can set up separate expectations for each table when developing their DLT pipeline.
- E. They cannot determine which table is dropping the records.
Answer: C
NEW QUESTION # 24
A data engineer is maintaining a data pipeline. Upon data ingestion, the data engineer notices that the source data is starting to have a lower level of quality. The data engineer would like to automate the process of monitoring the quality level.
Which of the following tools can the data engineer use to solve this problem?
- A. Unity Catalog
- B. Delta Live Tables
- C. Auto Loader
- D. Data Explorer
- E. Delta Lake
Answer: E
NEW QUESTION # 25
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?
- A. Unity Catalog
- B. Databricks SQL
- C. Delta Lake
- D. Auto Loader
- E. Data Explorer
Answer: D
NEW QUESTION # 26
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?
- A. Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log.
- B. Records that violate the expectation are added to the target dataset and recorded as invalid in the event log.
- C. Records that violate the expectation cause the job to fail.
- D. Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table.
- E. Records that violate the expectation are added to the target dataset and flagged as invalid in a field added to the target dataset.
Answer: B
NEW QUESTION # 27
Which of the following code blocks will remove the rows where the value in column age is greater than 25 from the existing Delta table my_table and save the updated table?
- A. SELECT * FROM my_table WHERE age > 25;
- B. UPDATE my_table WHERE age <= 25;
- C. UPDATE my_table WHERE age > 25;
- D. DELETE FROM my_table WHERE age > 25;
- E. DELETE FROM my_table WHERE age <= 25;
Answer: D
NEW QUESTION # 28
A data analysis team has noticed that their Databricks SQL queries are running too slowly when connected to their always-on SQL endpoint. They claim that this issue is present when many members of the team are running small queries simultaneously. They ask the data engineering team for help. The data engineering team notices that each of the team's queries uses the same SQL endpoint.
Which of the following approaches can the data engineering team use to improve the latency of the team's queries?
- A. They can turn on the Auto Stop feature for the SQL endpoint.
- B. They can turn on the Serverless feature for the SQL endpoint and change the Spot Instance Policy to
"Reliability Optimized." - C. They can increase the cluster size of the SQL endpoint.
- D. They can increase the maximum bound of the SQL endpoint's scaling range.
- E. They can turn on the Serverless feature for the SQL endpoint.
Answer: D
NEW QUESTION # 29
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?
- A. They can set up an Alert with a new webhook alert destination.
- B. They can set up an Alert with one-time notifications.
- C. They can set up an Alert with a custom template.
- D. They can set up an Alert without notifications.
- E. They can set up an Alert with a new email alert destination.
Answer: A
NEW QUESTION # 30
Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?
- A. The ability to distribute complex data operations
- B. The ability to manipulate the same data using a variety of languages
- C. The ability to collaborate in real time on a single notebook
- D. The ability to support batch and streaming workloads
- E. The ability to set up alerts for query failures
Answer: D
NEW QUESTION # 31
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?
- A. They can configure the clusters to be single-node
- B. They can configure the clusters to autoscale for larger data sizes
- C. They can use clusters that are from a cluster pool
- D. They can use endpoints available in Databricks SQL
- E. They can use jobs clusters instead of all-purpose clusters
Answer: E
NEW QUESTION # 32
A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables.
Which of the following commands should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?
- A. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
MERGE SELECT * FROM april_transactions; - B. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
UNION SELECT * FROM april_transactions; - C. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INNER JOIN SELECT * FROM april_transactions; - D. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INTERSECT SELECT * from april_transactions; - E. CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
OUTER JOIN SELECT * FROM april_transactions;
Answer: B
NEW QUESTION # 33
......
The GAQM Databricks-Certified-Data-Engineer-Associate exam is a certification exam designed for data engineers who want to prove their proficiency in designing and building data pipelines using Databricks. Databricks-Certified-Data-Engineer-Associate exam is designed to test the knowledge and skills of candidates in data engineering, big data processing and analytics, and cloud computing using Databricks.
Databricks-Certified-Data-Engineer-Associate exam is a comprehensive test of an individual's knowledge of Databricks and its related technologies, including Apache Spark, SQL, and Python. 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.
Accurate & Verified 2024 New Databricks-Certified-Data-Engineer-Associate Answers As Experienced in the Actual Test!: https://www.exam4tests.com/Databricks-Certified-Data-Engineer-Associate-valid-braindumps.html
Databricks-Certified-Data-Engineer-Associate Certification Sample Questions certification Exam: https://drive.google.com/open?id=1QLYWGnWryoVd7q60UNSIpV8pwdrC0maK