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Databricks Certified-Data-Engineer-Professional Exam Syllabus Topics:

Databricks Certified Data Engineer Professional Sample Questions:

Question 1

A data engineer needs to design an efficient pipeline that automatically processes new CSV files as they arrive in S3 storage. Which Databricks feature should the data engineer use to meet these requirements?

A. Traditional batch processing with scheduled Databricks Jobs
B. Streaming from cloud storage using standard Spark readStream with format ("csv") and format ("json")
C. Auto Loader with schema inference and evolution enabled
D. COPY INTO SQL command with parameters to track processed files

Question 2

A senior data engineer is planning large-scale data workflows. The current task is to identify the considerations that form a foundation for creating scalable data models that are essential for effective management of large datasets. The data engineering team has identified the core capabilities as part of a scalable data model to build a modern data platform and provided their reasoning for considering Delta Lake for review. The senior data engineer is responsible for identifying the recommendations that are not valid. Which key features can be ignored while evaluating Delta Lake?

A. Delta Lake works with various data formats (e.g., Parquet, JSON, CSV) and integrates well with Spark and Databricks tools.
B. Delta Lake optimizes metadata handling, efficiently managing billions of files and facilitating scalability to petabyte-scale datasets.
C. Delta Lake provides limited support for monitoring and troubleshooting data pipelines, so relevant partner tools have to be identified and set up for enhanced operational efficiency.
D. Delta Lake's capability to process data in both batch and streaming modes seamlessly, providing flexibility in data ingestion and processing.

Question 3

A job runs four independent tasks (X, Y, Z, W) in parallel to process regional sales data. The Data Engineering team recently updated its cluster policy to ban cost-prohibitive instance types. Task Y now fails due to the newly enforced cluster policy restricting the use of a specific instance type.
A data engineer needs to resolve the failure quickly without disrupting the other tasks. How should the data engineer resolve the failure of tasks?

A. Delete the failed run, disable the cluster policy, and re-execute all tasks.
B. Edit the global cluster policy to allow the restricted instance type, then re-run the entire job.
C. Manually create a new cluster for Task Y, update the job configuration, and trigger a full re-run.
D. Use "Repair run", override the cluster configuration for Task Y to use a permitted instance type, and let Databricks re-run only Task Y.

Question 4

What describes a primary technical challenge in ensuring consistent PII masking across all nodes in large-scale, distributed Databricks batch and streaming pipelines?

A. PII masking is only required for direct identifiers.
B. Native masking in Databricks automatically synchronizes with all downstream external Databricks systems.
C. Masking functions must be standardized and managed through Unity Catalog, with enforcement applied across all relevant datasets to avoid any data inconsistency.
D. Dynamic data masking is applied only at rest, so it does not affect query performance.

Question 5

A table named user_ltv is being used to create a view that will be used by data analysts on various teams. Users in the workspace are configured into groups, which are used for setting up data access using ACLs.
The user_ltv table has the following schema:
email STRING, age INT, ltv INT
The following view definition is executed:

An analyst who is not a member of the marketing group executes the following query:
SELECT * FROM email_ltv
Which statement describes the results returned by this query?

A. The email and ltv columns will be returned with the values in user itv.
B. The email, age. and ltv columns will be returned with the values in user ltv.
C. Only the email and ltv columns will be returned; the email column will contain the string
"REDACTED" in each row.
D. Three columns will be returned, but one column will be named "redacted" and contain only null values.
E. Only the email and itv columns will be returned; the email column will contain all null values.

Solutions: