An Einstein Analytics consultant is asked to add a new SalesTax field to a Product Sales dataset. The formula to calculate SalesTax is (SubTotal'CountyTax).
Which node should the consultant use in a Dataflow to calculate and insert SalesTax to the dataset?
A. append
B. computeExpression
C. augment
D. computeRelative
Creating an Einstein Discovery story involves:
A. Selecting a Dataset in Einstein Analytics, then clicking Create Story
B. Copying text from company reports and pasting into Einstein Discovery
C. Uploading a Microsoft?PowerPoint?presentation
D. Entering notes about the data
Philip adds a recently created Seed Bank Orders dataset to an Einstein Analytics app for which the Mosaic Seed Bank project team has the Viewer app role. How much data in the Seed Bank Orders dataset can a project team member see?
A. None of the data
B. Only rows designated by the Salesforce administrator
C. All rows and fields in the datasets
D. Only rows designated by the App Manager
Which of these standard deviations is for a curve that has values that are the most spread out away from the average?
A. 8
B. 1
C. 4
D. 16
What is another name for the type of insight that examines how one variable explains variation of the outcome variable?
A. First-order analysis
B. Second-order analysis
C. Third-order analysis
D. Spectrum analysis
E. Object-oriented analysis
In Einstein Discovery:
A. 'What Is The Difference' insights are comparative insights that help you better understand the relationships between explanatoryvariables and the goal (target outcome variable) in your story. These insights, based on a statistical analysis of your dataset, help you figure out which factors contribute to the biggest changes in the outcome variable. Einstein Discovery uses waterfallcharts to help you visualize comparisons in What Is The Difference insights.
B. 'Why It Happened' insights help you take a deeper look into the exact factors that led to an outcome. Why It Happened s/ Q insights drill deeper into the various factors that contributed to your story's goal. These insights are based on a statistical analysis of your dataset. Einstein Discovery uses waterfall charts to help you visualize Why It Happened insights.
C. 'Predictions and Improvements' insights help you explore what might happen in the future. For example, you can interactively perform "what if analyses in your story. Einstein Discovery provides you with predictions and suggested improvements based on a statistical analysis of your dataset and predictive analytics.To help you visualize these insights, Einstein Discovery uses:
-waterfall charts for predictions
-bar charts for suggested improvements
D. 'What Happened' insights are the primary insights in your story. They are descriptive insights that help you explore, at an y/ Q overview level, what factors contributed to the outcome, based on a statistical analysis of yourdataset. .Einstein Discovery uses bar charts to help you visualize What Happened insights.
In what order does Einstein Discoverypresent the insights that it uncovers?
A. Alphabetical, in ascending order
B. Alphabetical, in descending order
C. Insights that explain the most variation in the outcome variable, in ascending order
D. Insights that explain the most variation in theoutcome variable, in descending order
E. B and D
A consultant built an Einstein Analytics app for the Sales Operations team. The Sales Operations team wants to sharetheir app with other people at the company. The consultant recommends distributing the app as an Einstein Analytics template app.
What can the consultant do to give the Sales team more choices and options with future apps that are generated from the SalesOperations app?
A. Update contents in the Sales Operations app and changes will be pushed down to its generated apps.
B. Ensure the Sales team has the necessary permissions to customize their apps.
C. Create a configuration wizard for the app.
D. Update contents in the Sales Operations app and create new template versions of the app.
A consultant is working with a credit card company that needs help with ongoing fraudulent transactions. The company provides a representative sample dataset for the consultant to analyze in Einstein Discovery. The story's initial assessment shows that a third-party payment app is the source of these fraudulent transactions. However, the company rejects this assessment outcome, stating they have not had a partnership with this payment app long enough for it to be a concern.
What is the recommended next step to improve the story outcome?
A. Make adjustments to the story to better demonstrate that the third-party payment app is the culprit.
B. Use the credit card company's domain knowledge and exclude the third-party payment app from the story.
C. Explain to the company that the story has returned unbiasedresults and the initial assessment is accurate.
D. Ask the credit card company for a more comprehensive dataset to analyze.
What are the two main parts of a lens/exploration?
A. Query
B. Visualization
C. Dataset
D. Measure
E. Grouping
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