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

Section	Objectives
Databricks Lakehouse Platform Architecture	- Workspace and cluster architecture - Data governance concepts (Unity Catalog basics) - Medallion architecture (Bronze, Silver, Gold)
Delta Lake and Data Management	- Time travel and versioning - Delta Lake transactions and ACID properties - Schema evolution and enforcement
Data Ingestion and Processing	- ETL pipeline design patterns - Batch and streaming ingestion with Auto Loader - Structured Streaming fundamentals
Data Modeling and Transformation	- Spark SQL transformations - Dimensional modeling concepts - Performance optimization techniques
Production Pipelines and Orchestration	- Databricks Workflows - Job scheduling and monitoring - Error handling and recovery strategies

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Databricks Certified Data Engineer Professional Exam Sample Questions (Q155-Q160):

NEW QUESTION # 155
A platform team lead is responsible for automating the individual teams attribution towards SQL Warehouse usage. The requirement is to identify the SQL warehouse usage at the individual user's level and generate a daily report to be shared with an executive team that includes leaders from all business units. How should the platform lead generate an automated report that can be shared daily?

A. Restrict users from running any SQL query unless they provide all the query details so that the attribution can be calculated and shared with the executive team.
B. Use the system tables to capture the audit and billing usage data and create a dashboard with daily refresh schedules and shared with the executive team.
C. Use the system tables to capture the audit and billing usage data and share the queries with the executive team. This enables the executives to execute the query and see the latest results any time.
D. Let the users run the SQL query and then directly report the usage to the executives. The ownership of the SQL warehouse usage will be with the individual teams.

Answer: B

Explanation:
System tables provide authoritative audit and billing data needed for per-user SQL Warehouse attribution. Creating a dashboard with a scheduled daily refresh automates report generation and ensures executives receive consistent, up-to-date insights without needing to run queries themselves.

NEW QUESTION # 156
The view updates represents an incremental batch of all newly ingested data to be inserted or updated in the customers table.
The following logic is used to process these records.
MERGE INTO customers
USING (
SELECT updates.customer_id as merge_ey, updates .*
FROM updates
UNION ALL
SELECT NULL as merge_key, updates .*
FROM updates JOIN customers
ON updates.customer_id = customers.customer_id
WHERE customers.current = true AND updates.address <> customers.address ) staged_updates ON customers.customer_id = mergekey WHEN MATCHED AND customers. current = true AND customers.address <> staged_updates.address THEN UPDATE SET current = false, end_date = staged_updates.effective_date WHEN NOT MATCHED THEN INSERT (customer_id, address, current, effective_date, end_date) VALUES (staged_updates.customer_id, staged_updates.address, true, staged_updates.effective_date, null) Which statement describes this implementation?

A. The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.
B. The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.
C. The customers table is implemented as a Type 2 table; old values are maintained but marked as no longer current and new values are inserted.
D. The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.

Answer: C

Explanation:
The provided MERGE statement is a classic implementation of a Type 2 SCD in a data warehousing context. In this approach, historical data is preserved by keeping old records (marking them as not current) and adding new records for changes. Specifically, when a match is found and there's a change in the address, the existing record in the customers table is updated to mark it as no longer current (current = false), and an end date is assigned (end_date = staged_updates.effective_date). A new record for the customer is then inserted with the updated information, marked as current. This method ensures that the full history of changes to customer information is maintained in the table, allowing for time-based analysis of customer data.

NEW QUESTION # 157
A junior developer complains that the code in their notebook isn't producing the correct results in the development environment. A shared screenshot reveals that while they're using a notebook versioned with Databricks Repos, they're using a personal branch that contains old logic. The desired branch named dev-2.3.9 is not available from the branch selection dropdown.
Which approach will allow this developer to review the current logic for this notebook?

A. Use Repos to merge the current branch and the dev-2.3.9 branch, then make a pull request to sync with the remote repository
B. Use Repos to make a pull request use the Databricks REST API to update the current branch to dev-2.3.9
C. Use Repos to pull changes from the remote Git repository and select the dev-2.3.9 branch.
D. Merge all changes back to the main branch in the remote Git repository and clone the repo again
E. Use Repos to checkout the dev-2.3.9 branch and auto-resolve conflicts with the current branch

Answer: C

Explanation:
This is the correct answer because it will allow the developer to update their local repository with the latest changes from the remote repository and switch to the desired branch. Pulling changes will not affect the current branch or create any conflicts, as it will only fetch the changes and not merge them. Selecting the dev-2.3.9 branch from the dropdown will checkout that branch and display its contents in the notebook.

NEW QUESTION # 158
The Databricks CLI is use to trigger a run of an existing job by passing the job_id parameter. The response that the job run request has been submitted successfully includes a filed run_id.
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from Which statement describes what the number alongside this field represents?

A. The globally unique ID of the newly triggered run.
B. The number of times the job definition has been run in the workspace.
C. The total number of jobs that have been run in the workspace.
D. The job_id is returned in this field.
E. The job_id and number of times the job has been are concatenated and returned.

Answer: A

Explanation:
When triggering a job run using the Databricks CLI, the run_id field in the response represents a globally unique identifier for that particular run of the job. This run_id is distinct from the job_id.
While the job_id identifies the job definition and is constant across all runs of that job, the run_id is unique to each execution and is used to track and query the status of that specific job run within the Databricks environment. This distinction allows users to manage and reference individual executions of a job directly.

NEW QUESTION # 159
The Databricks CLI is use to trigger a run of an existing job by passing the job_id parameter. The response that the job run request has been submitted successfully includes a filed run_id.
Which statement describes what the number alongside this field represents?

A. The globally unique ID of the newly triggered run.
B. The number of times the job definition has been run in the workspace.
C. The total number of jobs that have been run in the workspace.
D. The job_id is returned in this field.
E. The job_id and number of times the job has been are concatenated and returned.

Answer: A

NEW QUESTION # 160
......

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