Databricks-Certified-Data-Engineer-Associate Free Practice Test

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?

1. A. They can set up separate expectations for each table when developing their DLT pipeline.
2. B. They cannot determine which table is dropping the records.
3. C. They can set up DLT to notify them via email when records are dropped.
4. D. They can navigate to the DLT pipeline page, click on each table, and view the data quality statistics.
5. E. They can navigate to the DLT pipeline page, click on the “Error” button, and review the present errors.

Correct Answer: D
To identify the table in a Delta Live Tables (DLT) pipeline where data is being dropped due to quality concerns, the data engineer can navigate to the DLT pipeline page, click on each table in the pipeline, and view the data quality statistics. These statistics often include information about records dropped, violations of expectations, and other data quality metrics. By examining the data quality statistics for each table in the pipeline, the data engineer can determine at which table the data is being dropped.

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?

1. A. dbfs:/user/hive/database/customer360
2. B. dbfs:/user/hive/warehouse
3. C. dbfs:/user/hive/customer360
4. D. More information is needed to determine the correct response

Correct Answer: B
dbfs:/user/hive/warehouse - which is the default location

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?

1. A. The VACUUM command was run on the table
2. B. The TIME TRAVEL command was run on the table
3. C. The DELETE HISTORY command was run on the table
4. D. The OPTIMIZE command was nun on the table
5. E. The HISTORY command was run on the table

Correct Answer: A
The VACUUM command in Delta Lake is used to clean up and remove unnecessary data files that are no longer needed for time travel or query purposes. When you run VACUUMwith certain retention settings, it can delete older data files, which might include versions of data that are older than the specified retention period. If the data engineer is unable to restore the table to a version that is 3 days old because the data files have been deleted, it's likely because the VACUUM command was run on the table, removing the older data files as part of data cleanup.

Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?

1. A. The ability to manipulate the same data using a variety of languages
2. B. The ability to collaborate in real time on a single notebook
3. C. The ability to set up alerts for query failures
4. D. The ability to support batch and streaming workloads
5. E. The ability to distribute complex data operations

Correct Answer: D
Delta Lake is a key component of the Databricks Lakehouse Platform that provides several benefits, and one of the most significant benefits is its ability to support both batch and streaming workloads seamlessly. Delta Lake allows you to process and analyze data in real-time (streaming) as well as in batch, making it a versatile choice for various data processing needs. While the other options may be benefits or capabilities of Databricks or the Lakehouse Platform in general, they are not specifically associated with Delta Lake.

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?

1. A. They can use endpoints available in Databricks SQL
2. B. They can use jobs clusters instead of all-purpose clusters
3. C. They can configure the clusters to be single-node
4. D. They can use clusters that are from a cluster pool
5. E. They can configure the clusters to autoscale for larger data sizes

Correct Answer: D
Cluster pools are a way to pre-provision clusters that are ready to use. This can reduce the start up time for clusters, as they do not have to be created from scratch. All-purpose clusters are not pre-provisioned, so they will take longer to start up. Jobs clusters are a type of cluster pool, but they are not the best option for this use case. Jobs clusters are designed for long-running jobs, and they can be more expensive than other types of cluster pools. Single-node clusters are the smallest type of cluster, and they will start up the fastest. However, they may not be powerful enough to run the Job's tasks. Autoscaling clusters can scale up or down based on demand. This can help to improve the start up time for clusters, as they will only be created when they are needed. However, autoscaling clusters can also be more expensive than other types of cluster pool https://docs.databricks.com/en/clusters/pool-best-practices.html