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The GAQM Databricks-Certified-Data-Engineer-Associate Exam is a certification exam that tests the ability of individuals to design and implement data-driven solutions using Databricks. Databricks-Certified-Data-Engineer-Associate exam is designed for data engineers who want to demonstrate their proficiency in working with data and analytics technologies. Databricks-Certified-Data-Engineer-Associate exam covers a range of topics, including data engineering, data modeling, data processing, and data analysis.

Databricks Certified Data Engineer Associate certification is widely recognized in the industry and is highly valued by employers. Earning this certification demonstrates to employers that a candidate has the skills and knowledge required to build and maintain data solutions on the Databricks platform. Databricks Certified Data Engineer Associate Exam certification can help professionals advance their careers and increase their earning potential.

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The Databricks Certified Data Engineer Associate Exam certification exam consists of 60 multiple-choice questions that need to be answered within 90 minutes. Databricks-Certified-Data-Engineer-Associate Exam is available in English and is delivered online through the GAQM testing platform. Databricks Certified Data Engineer Associate Exam certification exam is open to all individuals who are interested in data engineering and Databricks, regardless of their educational background.

Databricks Certified Data Engineer Associate Exam Sample Questions (Q56-Q61):

NEW QUESTION # 56
A data engineer wants to create a relational object by pulling data from two tables. The relational object does not need to be used by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to avoid copying and storing physical data.
Which of the following relational objects should the data engineer create?

A. Delta Table
B. Temporary view
C. View
D. Spark SQL Table
E. Database

Answer: B

Explanation:
Explanation
Temp view : session based Create temp view view_name as query All these are termed as session ended:
Opening a new notebook Detaching and reattaching a cluster Installing a python package Restarting a cluster

NEW QUESTION # 57
A single Job runs two notebooks as two separate tasks. A data engineer has noticed that one of the notebooks is running slowly in the Job's current run. The data engineer asks a tech lead for help in identifying why this might be the case.
Which of the following approaches can the tech lead use to identify why the notebook is running slowly as part of the Job?

A. They can navigate to the Tasks tab in the Jobs UI and click on the active run to review the processing notebook.
B. They can navigate to the Tasks tab in the Jobs UI to immediately review the processing notebook.
C. They can navigate to the Runs tab in the Jobs UI and click on the active run to review the processing notebook.
D. They can navigate to the Runs tab in the Jobs UI to immediately review the processing notebook.
E. There is no way to determine why a Job task is running slowly.

Answer: A

Explanation:
The Tasks tab in the Jobs UI shows the list of tasks that are part of a job, and allows the user to view the details of each task, such as the notebook path, the cluster configuration, the run status, and the duration. By clicking on the active run of a task, the user can access the Spark UI, the notebook output, and the logs of the task. These can help the user to identify the performance bottlenecks and errors in the task. The Runs tab in the Jobs UI only shows the summary of the job runs, such as the start time, the end time, the trigger, and the status. It does not provide the details of the individual tasks within a job run. References: Jobs UI, Monitor running jobs with a Job Run dashboard, How to optimize jobs performance

NEW QUESTION # 58
A data engineer only wants to execute the final block of a Python program if the Python variable day_of_week is equal to 1 and the Python variable review_period is True.
Which of the following control flow statements should the data engineer use to begin this conditionally executed code block?

A. if day_of_week == 1 and review_period == "True":
B. if day_of_week = 1 & review_period: = "True":
C. if day_of_week == 1 and review_period:
D. if day_of_week = 1 and review_period = "True":
E. if day_of_week = 1 and review_period:

Answer: C

Explanation:
In Python, the == operator is used to compare the values of two variables, while the = operator is used to assign a value to a variable. Therefore, option A and E are incorrect, as they use the = operator for comparison. Option B and C are also incorrect, as they compare the review_period variable to a string value "True", which is different from the boolean value True. Option D is the correct answer, as it uses the == operator to compare the day_of_week variable to the integer value 1, and the and operator to check if both conditions are true. If both conditions are true, then the final block of the Python program will be executed. Reference: [Python Operators], [Python If ... Else]

NEW QUESTION # 59
A data engineer wants to create a new table containing the names of customers that live in France.
They have written the following command:

A senior data engineer mentions that it is organization policy to include a table property indicating that the new table includes personally identifiable information (PII).
Which of the following lines of code fills in the above blank to successfully complete the task?

A. "COMMENT PII"
B. COMMENT "Contains PII"
C. PII
D. TBLPROPERTIES PII
E. There is no way to indicate whether a table contains PII.

Answer: D

NEW QUESTION # 60
Which of the following Git operations must be performed outside of Databricks Repos?

A. Clone
B. Commit
C. Merge
D. Push
E. Pull

Answer: C

Explanation:
Databricks Repos is a visual Git client and API in Databricks that supports common Git operations such as commit, pull, push, branch management, and visual comparison of diffs when committing1. However, merge is not supported in the Git dialog2. You need to use the Repos UI or your Git provider to merge branches3. Merge is a way to combine the commit history from one branch into another branch1. During a merge, a merge conflict is encountered when Git cannot automatically combine code from one branch into another. Merge conflicts require manual resolution before a merge can be completed1. Reference: 4: Run Git operations on Databricks Repos4, 1: CI/CD techniques with Git and Databricks Repos1, 3: Collaborate in Repos3, 2: Databricks Repos - What it is and how we can use it2.
Databricks Repos is a visual Git client and API in Databricks that supports common Git operations such as commit, pull, push, merge, and branch management. However, to clone a remote Git repository to a Databricks repo, you must use the Databricks UI or API. You cannot clone a Git repo using the CLI through a cluster's web terminal, as the files won't display in the Databricks UI1. Reference: 1: Run Git operations on Databricks Repos | Databricks on AWS2

NEW QUESTION # 61
......

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