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Oracle 1z0-1041-22 Exam With Confidence Using Practice Dumps

Exam Code:
1z0-1041-22
Exam Name:
Oracle Cloud Platform Enterprise Analytics 2022 Professional
Vendor:
Questions:
81
Last Updated:
Apr 30, 2025
Exam Status:
Stable
Oracle 1z0-1041-22

1z0-1041-22: Oracle Other Certification Exam 2025 Study Guide Pdf and Test Engine

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Oracle Cloud Platform Enterprise Analytics 2022 Professional Questions and Answers

Question 1

Which statement is true when migrating content from Oracle BI Enterprise Edition 12c to Oracle Analytics Cloud?

Options:

A.

At this time there is no option to migrate Oracle BI Enterprise Edition llg content to Oracle Analytics Cloud.

B.

Both the Oracle BI Enterprise Edition 12c Data Model and the Catalog must be migrated to Oracle Analytics Cloud. They cannot be migrated independently.

C.

You can migrate a snapshot from Oracle BI Enterprise Edition 12c to Oracle Analytics Cloud.

D.

You can only migrate an Oracle BI Enterprise Edition 12c Data Model to Oracle Analytics Cloud. Catalog migration is not allowed.

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Question 2

What are two incorrect steps when creating pixel perfect reports with Bl Publisher?

Options:

A.

Generate and save to a folder in the Presentation Catalog a sample set of data that can be used for configuring and testing the report.

B.

Define a data model to set the business view of the data, join data sets, and create custom measures.

C.

Create connections to sources, some of which include Oracle l0g/llg, Oracle BI Server, JDBC, and MS SQL Server 2005/2008.

D.

Test connections between BI Publisher and configured sources using Oracle Fusion Middleware Control.

Question 3

Which two statements are true about a segment as defined in the Oracle Analytics Cloud machine learning functionality?

Options:

A.

It Is a component of the output from the Explain functionality.

B.

It Is a component of a data flow sequence.

C.

It is the resulting data set after applying a filter in a data flow.

D.

It is a statistically determined group of data points that may contribute to predicting the value of an attribute of interest.