Databricks-Certified-Data-Engineer-Associate Practice Test Questions Answers Updated 102 Questions [Q19-Q36]

Q19. 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?

Q20. Which of the following commands will return the location of database customer360?

Q21. A data engineer has realized that the data files associated with a Delta table are incredibly small. They want to compact the small files to form larger files to improve performance.
Which of the following keywords can be used to compact the small files?

Q22. A data engineer has a Python notebook in Databricks, but they need to use SQL to accomplish a specific task within a cell. They still want all of the other cells to use Python without making any changes to those cells.
Which of the following describes how the data engineer can use SQL within a cell of their Python notebook?

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?

Q24. Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?

Q25. 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?

Q26. A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).
Which of the following code blocks creates this SQL UDF?

Q27. 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?

Q28. Which of the following describes the relationship between Bronze tables and raw data?

Q29. Which of the following is a benefit of the Databricks Lakehouse Platform embracing open source technologies?

Q30. Which of the following must be specified when creating a new Delta Live Tables pipeline?

Q31. A data engineer has developed a data pipeline to ingest data from a JSON source using Auto Loader, but the engineer has not provided any type inference or schema hints in their pipeline. Upon reviewing the data, the data engineer has noticed that all of the columns in the target table are of the string type despite some of the fields only including float or boolean values.
Which of the following describes why Auto Loader inferred all of the columns to be of the string type?

Q32. Which of the following commands will return the number of null values in the member_id column?

Q33. 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?

Q34. A data engineer needs to determine whether to use the built-in Databricks Notebooks versioning or version their project using Databricks Repos.
Which of the following is an advantage of using Databricks Repos over the Databricks Notebooks versioning?

Q35. A data engineer has developed a data pipeline to ingest data from a JSON source using Auto Loader, but the engineer has not provided any type inference or schema hints in their pipeline. Upon reviewing the data, the data engineer has noticed that all of the columns in the target table are of the string type despite some of the fields only including float or boolean values.
Which of the following describes why Auto Loader inferred all of the columns to be of the string type?

Q36. Which of the following benefits is provided by the array functions from Spark SQL?