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Databricks Databricks-Certified-Professional-Data-Engineer Dumps Questions Answers

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Databricks-Certified-Professional-Data-Engineer
Last Update: Apr 23, 2024
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Databricks Databricks-Certified-Professional-Data-Engineer Exam Dumps FAQs

The Databricks Databricks-Certified-Professional-Data-Engineer exam is ideal for experienced data engineers seeking to validate their proficiency in building and managing advanced data pipelines on the Databricks Lakehouse Platform. If you possess strong skills in Apache Spark, Delta Lake, MLflow, and Databricks tools, this certification will showcase your expertise to potential employers.
The Databricks Databricks-Certified-Professional-Data-Engineer Exam is a proctored certification exam that consists of 60 multiple-choice questions. The time limit for the exam is 120 minutes.
There are no prerequisites for taking the Databricks Databricks-Certified-Professional-Data-Engineer Exam. However, related training is highly recommended.

The Databricks Databricks-Certified-Professional-Data-Engineer Exam assesses an individual’s ability to use Databricks to perform advanced data engineering tasks. The exam covers:

  • Databricks Tooling (20%)
  • Data Processing (30%)
  • Data Modeling (20%)
  • Security and Governance (10%)
  • Monitoring and Logging (10%)
  • Testing and Deployment (10%)
  • The Databricks-Certified-Professional-Data-Engineer Exam assesses an individual’s ability to use Databricks to perform advanced data engineering tasks, including building optimized and cleaned ETL pipelines, modeling data into a lakehouse, and ensuring that data pipelines are secure, reliable, monitored, and tested before deployment. The exam covers Databricks Tooling, Data Processing, Data Modeling, Security and Governance, Monitoring and Logging, and Testing and Deployment.
  • The Databricks-Certified-Professional-Data-Scientist Exam assesses an individual’s ability to use Databricks to perform advanced data science tasks, including building and deploying machine learning models, using MLflow to track experiments, and using Delta Lake to manage data. The exam covers Databricks Tooling, Data Processing, Machine Learning, and Data Management.

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Databricks Certified Data Engineer Professional Exam Questions and Answers

Questions 1

A Databricks SQL dashboard has been configured to monitor the total number of records present in a collection of Delta Lake tables using the following query pattern:

SELECT COUNT (*) FROM table -

Which of the following describes how results are generated each time the dashboard is updated?

Options:

A.

The total count of rows is calculated by scanning all data files

B.

The total count of rows will be returned from cached results unless REFRESH is run

C.

The total count of records is calculated from the Delta transaction logs

D.

The total count of records is calculated from the parquet file metadata

E.

The total count of records is calculated from the Hive metastore

Questions 2

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.

Which statement describes this implementation?

Options:

A.

The customers table is implemented as a Type 3 table; old values are maintained as a new column alongside the current value.

B.

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.

C.

The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.

D.

The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.

E.

The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.

Questions 3

The data architect has mandated that all tables in the Lakehouse should be configured as external (also known as "unmanaged") Delta Lake tables.

Which approach will ensure that this requirement is met?

Options:

A.

When a database is being created, make sure that the LOCATION keyword is used.

B.

When configuring an external data warehouse for all table storage, leverage Databricks for all ELT.

C.

When data is saved to a table, make sure that a full file path is specified alongside the Delta format.

D.

When tables are created, make sure that the EXTERNAL keyword is used in the CREATE TABLE statement.

E.

When the workspace is being configured, make sure that external cloud object storage has been mounted.

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