1z0-1041-22 無料問題集「Oracle Cloud Platform Enterprise Analytics 2022 Professional」

（A）LM-TD

（B）PY-TD

（C）Q-T-D

（D）Y-T-D

（E）D-T-Y

（A）The standard deviation of the data

（B）The average of the data

（C）The maximum of the data

（D）The median of the data

（A）Create a scenario using the required model.

（B）Use the machine learning model visualization.

（C）Create a data sequence.

（D）Create a custom calculation.

（A）Create a scatter plot of the two numeric values and choose a value of interest as the category (points).

（B）Create a line chart with multiple reference lines.

（C）Use a box plot with trellising.

（D）Create multiple pie charts.

（A）After working in the sandbox environment, you can commit changes to the base environment or even to another sandbox target.

（B）The sandbox dimension has one base member and multiple sandbox members.

（C）Initially, the state of each sandbox member is #missing.

（D）Using the sandbox dimension has storage overhead that would be required to replicate data from the base environment.

（E）When you submit changes to a base member, changes are seen and stored in each sandbox member.

（A）Analyses can be created with measures from multiple physical tables defined as sources in a single logical fact table.

（B）Analyses cannot be created from multiple subject areas even though they contain common, conformed dimensions.

（C）Analyses can be created from multiple business models as long as they contain common, conformed dimensions.

（D）Analyses can be created from multiple subject areas as long as at least one metric Is Included from each, and the Dimensionality Flag is enabled.

（A）a table that reports the occurrences of false positives, false negatives, true positives, and true negatives for a machine learning model

（B）a table that reports the occurrences of negative positives, false negatives, true positives, and positive negatives for a machine learning model

（C）a table that reports the occurrences of higher positives, false negatives, lower positives, and true negatives for a machine learning model

（D）a table that reports the occurrences of upper positives, lower negatives, mid positives, and true negatives for a machine learning model

（A）Measures

（B）REST APIs

（C）Nulls

（D）Dimension Keys