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

• A.It is the resulting data set after applying a filter in a data flow.
• B.It is a statistically determined group of data points that may contribute to predicting the value of an attribute of interest.
• C.It Is a component of the output from the Explain functionality.
• D.It Is a component of a data flow sequence.

Comment: *

Name: *

Email: *

Verification: *

Your customer has a hybrid aggregate Essbase cube. They want to be able to model what-if scenarios with hypothetical data and are considering using the Sandbox dimension.
Which two statements represent correct functionality of the Sandbox dimension?

• A.Using the sandbox dimension has storage overhead that would be required to replicate data from the base environment.
• B.The sandbox dimension has one base member and multiple sandbox members.
• C.Initially, the state of each sandbox member is #missing.
• D.When you submit changes to a base member, changes are seen and stored in each sandbox member.
• E.After working in the sandbox environment, you can commit changes to the base environment or even to another sandbox target.

Comment: *

Name: *

Email: *

Verification: *

Select two correct editions of Oracle Analytics Cloud.

• A.Big Data Edition
• B.SaaS Edition
• C.Data Lake Edition
• D.BI Cloud Service Edition
• E.Standard Edition

Comment: *

Name: *

Email: *

Verification: *

You have added new columns to the source table. What should you do to include the new columns in your data model?

• A.Add Columns from Database
• B.Connect to Tables
• C.Update Data Model
• D.Synchronize with Database

Comment: *

Name: *

Email: *

Verification: *

You've created a machine learning model and investigated how accurate it is. How should you use it in Oracle Analytics Cloud?

• A.Create a custom calculation based on a related formula.
• B.Use a data flow with an Apply Model step and save as a new data set.
• C.Use a data flow with a Commit Model step and save as a new data set.
• D.Embed the model into a data flow sequence.
• E.Create a data flow with a cumulative value prediction.

Comment: *

Name: *

Email: *

Verification: *