Databricks-Certified-Data-Engineer-Associate PDF Dumps Real 2026 Recently Updated Questions

Released Databricks Databricks-Certified-Data-Engineer-Associate Updated Questions PDF

One of the unique features of the Databricks Certified Data Engineer Associate certification is that it is focused on Databricks, a cloud-based big data processing platform. Databricks is becoming increasingly popular among data professionals, and the certification is designed to test individuals' knowledge of this platform. This makes the certification especially valuable for individuals who work with Databricks or plan to work with it in the future.

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. The Databricks Certified Data Engineer Associate certification is highly valued in the data engineering industry and is recognized globally. Databricks Certified Data Engineer Associate Exam certification covers various topics related to data engineering, big data processing and analytics, and cloud computing using Databricks. Databricks Certified Data Engineer Associate Exam certification is ideal for data engineers who work with Databricks and want to advance their careers in data engineering.

 

NEW QUESTION # 57
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. Delta Live Tables
• B. Unity Catalog
• C. Auto Loader
• D. Data Explorer
• E. Delta Lake

Answer: A

Explanation:
Explanation
https://docs.databricks.com/delta-live-tables/expectations.html
Delta Live Tables is a tool provided by Databricks that can help data engineers automate the monitoring of data quality. It is designed for managing data pipelines, monitoring data quality, and automating workflows.
With Delta Live Tables, you can set up data quality checks and alerts to detect issues and anomalies in your data as it is ingested and processed in real-time. It provides a way to ensure that the data quality meets your desired standards and can trigger actions or notifications when issues are detected. While the other tools mentioned may have their own purposes in a data engineeringenvironment, Delta Live Tables is specifically designed for data quality monitoring and automation within the Databricks ecosystem.

NEW QUESTION # 58
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?

• A. The PARQUET file format does not support COPY INTO.
• B. The previous day's file has already been copied into the table.
• C. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.
• D. The COPY INTO statement requires the table to be refreshed to view the copied rows.
• E. The names of the files to be copied were not included with the FILES keyword.

Answer: B

Explanation:
Explanation
https://docs.databricks.com/en/ingestion/copy-into/index.html The COPY INTO SQL command lets you load data from a file location into a Delta table. This is a re-triable and idempotent operation; files in the source location that have already been loaded are skipped. if there are no new records, the only consistent choice is C no new files were loaded because already loaded files were skipped.

NEW QUESTION # 59
A data engineer needs to parse only png files in a directory that contains files with different suffixes. Which code should the data engineer use to achieve this task?

• A.
• B.
• C.
• D.

Answer: D

NEW QUESTION # 60
A data engineering team has noticed that their Databricks SQL queries are running too slowly when they are submitted to a non-running SQL endpoint. The data engineering team wants this issue to be resolved.
Which of the following approaches can the team use to reduce the time it takes to return results in this scenario?

• A. They can turn on the Serverless feature for the SQL endpoint and change the Spot Instance Policy to
  "Reliability Optimized."
• B. They can increase the cluster size of the SQL endpoint.
• C. They can turn on the Auto Stop feature for the SQL endpoint.
• D. They can turn on the Serverless feature for the SQL endpoint.
• E. They can increase the maximum bound of the SQL endpoint's scaling range

Answer: B

Explanation:
Explanation
https://www.databricks.com/blog/2022/03/10/top-5-databricks-performance-tips.html

NEW QUESTION # 61
Which of the following describes the relationship between Bronze tables and raw data?

• A. Bronze tables contain aggregates while raw data is unaggregated.
• 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 more truthful data than raw data.
• E. Bronze tables contain raw data with a schema applied.

Answer: E

Explanation:
Explanation
The Bronze layer is where we land all the data from external source systems. 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 focus in this layer is quick Change Data Capture and the ability to provide an historical archive of source (cold storage), data lineage, auditability, reprocessing if needed without rereading the data from the source system.https://www.databricks.com/glossary/medallion-architecture#:~:text=Bronze%20layer%20%28raw%20d

NEW QUESTION # 62
A new data engineering team team has been assigned to an ELT project. The new data engineering team will need full privileges on the table sales to fully manage the project.
Which command can be used to grant full permissions on the database to the new data engineering team?

• A. GRANT ALL PRIVILEGES ON TABLE team TO sales;
• B. GRANT SELECT ON TABLE sales TO team;
• C. GRANT SELECT CREATE MODIFY ON TABLE sales TO team;
• D. grant all privileges on table sales TO team;

Answer: D

Explanation:
To grant full privileges on a table such as 'sales' to a group like 'team', the correct SQL command in Databricks is:
GRANT ALL PRIVILEGES ON TABLE sales TO team;
This command assigns all available privileges, including SELECT, INSERT, UPDATE, DELETE, and any other data manipulation or definition actions, to the specified team. This is typically necessary when a team needs full control over a table to manage and manipulate it as part of a project or ongoing maintenance.
References:Databricks documentation on SQL permissions: SQL Permissions in Databricks

NEW QUESTION # 63
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
  UNION SELECT * FROM april_transactions;
• B. CREATE TABLE all_transactions AS
  SELECT * FROM march_transactions
  INTERSECT SELECT * from april_transactions;
• C. CREATE TABLE all_transactions AS
  SELECT * FROM march_transactions
  MERGE SELECT * FROM april_transactions;
• D. CREATE TABLE all_transactions AS
  SELECT * FROM march_transactions
  OUTER JOIN SELECT * FROM april_transactions;
• E. CREATE TABLE all_transactions AS
  SELECT * FROM march_transactions
  INNER JOIN SELECT * FROM april_transactions;

Answer: A

NEW QUESTION # 64
Which file format is used for storing Delta Lake Table?

• A. Delta
• B. JSON
• C. Parquet
• D. SV

Answer: C

NEW QUESTION # 65
A data engineer needs to process SQL queries on a large dataset with fluctuating workloads. The workload requires automatic scaling based on the volume of queries, without the need to manage or provision infrastructure. The solution should be cost-efficient and charge only for the compute resources used during query execution.
Which compute option should the data engineer use?

• A. Databricks Runtime for ML
• B. Databricks Jobs
• C. Serverless SQL Warehouse
• D. Databricks SQL Analytics

Answer: C

NEW QUESTION # 66
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?

• A. The PARQUET file format does not support COPY INTO.
• B. The previous day's file has already been copied into the table.
• C. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.
• D. The COPY INTO statement requires the table to be refreshed to view the copied rows.
• E. The names of the files to be copied were not included with the FILES keyword.

Answer: B

Explanation:
The COPY INTO statement is an idempotent operation, which means that it will skip any files that have already been loaded into the target table1. This ensures that the data is not duplicated or corrupted by multiple attempts to load the same file. Therefore, if the data engineer runs the same command every day without specifying the names of the files to be copied with the FILES keyword or a glob pattern with the PATTERN keyword, the statement will only copy the first file that matches the source location and ignore the rest. To avoid this problem, the data engineer should either use the FILES or PATTERN keywords to filter the files to be copied based on the date or some other criteria, or delete the files from the source location after they are copied into the table2. References: 1: COPY INTO | Databricks on AWS 2: Get started using COPY INTO to load data | Databricks on AWS

NEW QUESTION # 67
A data engineer needs to provide access to a group named manufacturing-team. The team needs privileges to create tables in the quality schema.
Which set of SQL commands will grant a group named manufacturing-team to create tables in a schema named production with the parent catalog named manufacturing with the least privileges?

• A.
• B.
• C.
• D.

Answer: B

NEW QUESTION # 68
A data engineer needs access to a table new_table, but they do not have the correct permissions. They can ask the table owner for permission, but they do not know who the table owner is.
Which of the following approaches can be used to identify the owner of new_table?

• A. All of these options can be used to identify the owner of the table
• B. Review the Owner field in the table's page in the cloud storage solution
• C. Review the Permissions tab in the table's page in Data Explorer
• D. There is no way to identify the owner of the table
• E. Review the Owner field in the table's page in Data Explorer

Answer: E

NEW QUESTION # 69
A data engineer wants to create a new table containing the names of customers who live in France.
They have written the following command:
CREATE TABLE customersInFrance
_____ AS
SELECT id,
firstName,
lastName
FROM customerLocations
WHERE country = 'FRANCE';
A senior data engineer mentions that it is organization policy to include a table property indicating that the new table includes personally identifiable information (Pll).
Which line of code fills in the above blank to successfully complete the task?

• A. TBLPROPERTIES PII
• B. COMMENT "Contains PIT
• C. "COMMENT PII"
• D. 0

Answer: A

Explanation:
To include a property indicating that a table contains personally identifiable information (PII), the TBLPROPERTIES keyword is used in SQL to add metadata to a table. The correct syntax to define a table property for PII is as follows:
CREATE TABLE customersInFrance
USING DELTA
TBLPROPERTIES ('PII' = 'true')
AS
SELECT id,
firstName,
lastName
FROM customerLocations
WHERE country = 'FRANCE';
The TBLPROPERTIES ('PII' = 'true') line correctly sets a table property that tags the table as containing personally identifiable information. This is in accordance with organizational policies for handling sensitive information.
References:Databricks documentation on Delta Lake: Delta Lake on Databricks

NEW QUESTION # 70
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 a limit to the number of DBUs that are consumed by the SQL Endpoint.
• B. They can set a limit to the number of individuals that are able to manage the query's refresh schedule.
• C. They can set the query's refresh schedule to end after a certain number of refreshes.
• D. They can set the query's refresh schedule to end on a certain date in the query scheduler.
• E. They cannot ensure the query does not cost the organization money beyond the first week of the project's release.

Answer: D

NEW QUESTION # 71
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 respond more quickly to ad-hoc requests
• D. Both teams would autoscale their work as data size evolves
• E. Both teams would reorganize to report to the same department

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. Reference: 1: What is a Data Lakehouse? - Databricks 2: What is a data lakehouse? | IBM

NEW QUESTION # 72
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 USAGE ON DATABASE customers TO team;
• B. GRANT SELECT CREATE MODIFY USAGE PRIVILEGES ON DATABASE customers TO team;
• C. GRANT ALL PRIVILEGES ON DATABASE team TO customers;
• D. GRANT ALL PRIVILEGES ON DATABASE customers TO team;
• E. GRANT SELECT PRIVILEGES ON DATABASE customers TO teams;

Answer: D

Explanation:
Explanation
To grant full privileges on the database "customers" to the new data engineering team, you can use the GRANT ALL PRIVILEGES command as shown in option E. This command provides the team with all possible privileges on the specified database, allowing them to fully manage it.

NEW QUESTION # 73
A dataset has been defined using Delta Live Tables and includes an expectations clause:
CONSTRAINT valid_timestamp EXPECT (timestamp > '2020-01-01') ON VIOLATION FAIL UPDATE 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: C

Explanation:
The expected behavior when a batch of data containing data that violates the expectation is processed is that the job will fail. This is because the expectation clause has the ON VIOLATION FAIL UPDATE option, which means that if any record in the batch does not meet the expectation, the entire batch will be rejected and the job will fail. This option is useful for enforcing strict data quality rules and preventing invalid data from entering the target dataset.
Option A is not correct, as the ON VIOLATION FAIL UPDATE option does not drop the records that violate the expectation, but fails the entire batch. To drop the records that violate the expectation and record them as invalid in the event log, the ON VIOLATION DROP RECORD option should be used.
Option C is not correct, as the ON VIOLATION FAIL UPDATE option does not drop the records that violate the expectation, but fails the entire batch. To drop the records that violate the expectation and load them into a quarantine table, the ON VIOLATION QUARANTINE RECORD option should be used.
Option D is not correct, as the ON VIOLATION FAIL UPDATE option does not add the records that violate the expectation, but fails the entire batch. To add the records that violate the expectation and record them as invalid in the event log, the ON VIOLATION LOG RECORD option should be used.
Option E is not correct, as the ON VIOLATION FAIL UPDATE option does not add the records that violate the expectation, but fails the entire batch. To add the records that violate the expectation and flag them as invalid in a field added to the target dataset, the ON VIOLATION FLAG RECORD option should be used.
References:
* Delta Live Tables Expectations
* [Databricks Data Engineer Professional Exam Guide]

NEW QUESTION # 74
A data engineer needs to create a table in Databricks using data from a CSV file at location /path/to/csv.
They run the following command:

Which of the following lines of code fills in the above blank to successfully complete the task?

• A. FROM "path/to/csv"
• B. USING DELTA
• C. FROM CSV
• D. USING CSV
• E. None of these lines of code are needed to successfully complete the task

Answer: D

NEW QUESTION # 75
......

The Databricks Databricks-Certified-Data-Engineer-Associate exam has 50 multiple-choice questions, and the candidate has 90 minutes to complete it. It is an online exam that can be taken at any time and from anywhere in the world. The questions in the exam are designed to test the candidate's ability to handle real-world data engineering challenges. Databricks-Certified-Data-Engineer-Associate exam also tests the candidate's understanding of the Databricks platform and how it can be used to solve data engineering problems.

 

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