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Oracle 1Z0-1041-21 Exam Syllabus Topics:

Oracle Cloud Platform Enterprise Analytics 2021 Specialist Sample Questions:

1. A customer wants to build a Block Storage (BSO) cube which has 8 standard dimensions and 2 attribute dimensions.
How many dimension worksheets will the application workbook have?

A) 12 dimension worksheets
B) 8 dimension worksheets
C) 9 dimension worksheets
D) 1 dimension worksheet
E) 10 dimension worksheets

2. You have created a visualization of revenue data over time. It displays some seasonality (e.g. high revenue around typical holiday periods) but there is no obvious pattern to the data overall. In which two ways can you start to get insight from this data?

A) Add a filter to remove the oldest data.
B) Create a reference line which displays the average revenue.
C) Create a trend line.
D) Create a column trellis over the prominent dimension value.

3. How should you determine the accuracy of a machine learning model created in Oracle AnalyticsCloud?

A) Use the debug option in the data flow where the model was created.
B) Run the machine learning model with various filter values applied.
C) Open the Inspect dialog for a given machine learning model and review the F1 score.
D) Create a data flow that Includes a histogram.

4. Which of the following cannot be done with Data Visualization to shape stories?

A) Create filters to focus upon pertinent data points.
B) Multiple projects can be combined into one project by clicking on theShare icon in the Narrate menu bar.
C) Visual canvases can beresized and the Auto Fit setting can be disabled.
D) Enhance narrative transition by rearranging and/or hiding Insight canvases.

5. The data loads for your Essbase cube are taking many hours, due to which the cube is unavailable to theuser for extended periods every day. You are assigned the task of optimizing the data load process.
Which are four optimization steps?

A) switching from multiple data fields to a single data field
B) using Parallel load
C) loading from the Essbase server
D) making the data source as small as possible by eliminating redundancy
E) grouping the data source by sparse-dimensionmember combination
F) positioning data in reverse order as the outline

Solutions: