Databricks-Certified-Professional-Data-Engineer Valid Exam Notes - Databricks-Certified-Professional-Data-Engineer Flexible Testing Engine

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Databricks Databricks-Certified-Professional-Data-Engineer Exam Overview:

Certification Vendor:	Databricks
Exam Name:	Databricks Certified Professional Data Engineer Exam
Exam Number:	Databricks-Certified-Professional-Data-Engineer
Certificate Validity Period:	2 years
Available Languages:	Portuguese (Brazil), Korean, Japanese, English
Exam Format:	Multiple Choice
Related Certifications:	Databricks Certified Associate Data Engineer
Exam Duration:	120 minutes
Real Exam Qty:	59
Passing Score:	70%
Exam Price:	USD 200
Recommended Training:	Databricks Data Engineer Professional Training
Exam Registration:	Databricks Official Certification Registration
Sample Questions:	Databricks Databricks-Certified-Professional-Data-Engineer Sample Questions
Exam Way:	Online proctored or onsite test center
Pre Condition:	No mandatory prerequisites; 1+ year hands-on experience and related training highly recommended
Official Syllabus URL:	https://www.databricks.com/learn/certification/data-engineer-professional

>> Databricks-Certified-Professional-Data-Engineer Valid Exam Notes <<

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Databricks Certified Professional Data Engineer exam is a hands-on exam that requires the candidate to complete a set of tasks using Databricks. Databricks-Certified-Professional-Data-Engineer Exam evaluates the candidate's ability to design and implement data pipelines, work with data sources and sinks, and perform transformations using Databricks. Databricks-Certified-Professional-Data-Engineer exam also tests the candidate's ability to optimize and tune data pipelines for performance and reliability.

Databricks Certified Professional Data Engineer certification exam is designed to test the knowledge and skills of data engineers who work with Databricks. Databricks is a cloud-based platform that provides a unified analytics engine for big data processing and machine learning. It is used by data engineers to manage data pipelines, extract insights from data, and build machine learning models. Databricks Certified Professional Data Engineer Exam certification exam is a comprehensive assessment of the candidate's ability to use Databricks effectively for data engineering tasks.

Databricks Certified Professional Data Engineer Exam Sample Questions (Q210-Q215):

NEW QUESTION # 210
A table is registered with the following code:

Both users and orders are Delta Lake tables. Which statement describes the results of querying recent_orders?

A. All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.
B. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
C. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
D. Results will be computed and cached when the table is defined; these cached results will incrementally update as new records are inserted into source tables.
E. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.

Answer: A

NEW QUESTION # 211
The data engineer team has been tasked with configured connections to an external database that does not have a supported native connector with Databricks. The external database already has data security configured by group membership. These groups map directly to user group already created in Databricks that represent various teams within the company.
A new login credential has been created for each group in the external database. The Databricks Utilities Secrets module will be used to make these credentials available to Databricks users.
Assuming that all the credentials are configured correctly on the external database and group membership is properly configured on Databricks, which statement describes how teams can be granted the minimum necessary access to using these credentials?

A. No additional configuration is necessary as long as all users are configured as administrators in the workspace where secrets have been added.
B. "Read" permissions should be set on a secret scope containing only those credentials that will be used by a given team.
C. "Manage" permission should be set on a secret scope containing only those credentials that will be used by a given team.
D. ''Read'' permissions should be set on a secret key mapped to those credentials that will be used by a given team.

Answer: B

Explanation:
In Databricks, using the Secrets module allows for secure management of sensitive information such as database credentials. Granting 'Read' permissions on a secret key that maps to database credentials for a specific team ensures that only members of that team can access these credentials. This approach aligns with the principle of least privilege, granting users the minimum level of access required to perform their jobs, thus enhancing security.
:
Databricks Documentation on Secret Management: Secrets

NEW QUESTION # 212
Which statement describes the correct use of pyspark.sql.functions.broadcast?

A. It marks a column as having low enough cardinality to properly map distinct values to available partitions, allowing a broadcast join.
B. It caches a copy of the indicated table on attached storage volumes for all active clusters within a Databricks workspace.
C. It marks a DataFrame as small enough to store in memory on all executors, allowing a broadcast join.
D. It caches a copy of the indicated table on all nodes in the cluster for use in all future queries during the cluster lifetime.
E. It marks a column as small enough to store in memory on all executors, allowing a broadcast join.

Answer: C

Explanation:
Explanation
https://spark.apache.org/docs/3.1.3/api/python/reference/api/pyspark.sql.functions.broadcast.html

NEW QUESTION # 213
Which of the following tool provides Data Access control, Access Audit, Data Lineage, and Data discovery?

A. DELTA LIVE Pipelines
B. Lakehouse
C. Unity Catalog
D. Data Governance
E. DELTA lake

Answer: C

NEW QUESTION # 214
A Delta table of weather records is partitioned by date and has the below schema:
date DATE, device_id INT, temp FLOAT, latitude FLOAT, longitude FLOAT
To find all the records from within the Arctic Circle, you execute a query with the below filter:
latitude > 66.3
Which statement describes how the Delta engine identifies which files to load?

A. The Delta log is scanned for min and max statistics for the latitude column
B. All records are cached to an operational database and then the filter is applied
C. The Hive metastore is scanned for min and max statistics for the latitude column
D. All records are cached to attached storage and then the filter is applied
E. The Parquet file footers are scanned for min and max statistics for the latitude column

Answer: A

Explanation:
This is the correct answer because Delta Lake uses a transaction log to store metadata about each table, including min and max statistics for each column in each data file. The Delta engine can use this information to quickly identify which files to load based on a filter condition, without scanning the entire table or the file footers. This is called data skipping and it can improve query performance significantly. Verified Reference: [Databricks Certified Data Engineer Professional], under "Delta Lake" section; [Databricks Documentation], under "Optimizations - Data Skipping" section.
In the Transaction log, Delta Lake captures statistics for each data file of the table. These statistics indicate per file:
- Total number of records
- Minimum value in each column of the first 32 columns of the table
- Maximum value in each column of the first 32 columns of the table
- Null value counts for in each column of the first 32 columns of the table When a query with a selective filter is executed against the table, the query optimizer uses these statistics to generate the query result. it leverages them to identify data files that may contain records matching the conditional filter.
For the SELECT query in the question, The transaction log is scanned for min and max statistics for the price column

NEW QUESTION # 215
......

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