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Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions (Q78-Q83):

NEW QUESTION # 78
A company created a dataset called myExternalDataset. It contains a dimension, called UserRegion, that is populated by the standard User object's picklist: Region.
The company has security requirements for this dataset:
1. Only a subset of users should be able to access the dataset.
2. Users who can access the dataset should see only data that belongs to their region.
In which two ways can an Einstein Analytics consultant help them implement these requirements? Choose 2 answers

• A. Create a sharing rule in Salesforce based on the Region field in the user object and set the dataset to inherit sharing from Salesforce.
• B. Save the dataset under a new application and give "viewer" access to a public group containing the list of users allowed to see the dataset.
• C. Save the dataset under "My Private App" so only a subset of selected users can access the dataset.
• D. Use a security predicate in the dataset so users can see only rows belonging to their respective regions.

Answer: B,D

NEW QUESTION # 79
A consultant is asked to configured a user to view a dashboard, within a designated app, without the ability to create and save lenses.
After adding the user to the app, which action should the consultant take to implement this requirement?

• A. Ensure the user has the Analytics permission
• B. Assign the Manager role the user
• C. Assign the view role to the user
• D. Assign the Editor role the user

Answer: A

NEW QUESTION # 80
How do you create a regression timeseries?

Answer:

Explanation:
In SAQL, use the timeseries function with the following arguments: Partition (the group_by piece), Seasonality (set to 12 to get yearly seasonality).

NEW QUESTION # 81
Max Analytics API calls per user per hour

• A. 10,000
• B. 100,000
• C. 50,000
• D. 5,000

Answer: A

NEW QUESTION # 82
A dataset for building the Einstein Discovery story contains 72 fields that are potentially relevant predictors.
Which approach is considered best practice to assess the top predictors in order to get to a meaningful and robust model?

• A. This dataset is too big and cannot be used in Einstein Discovery. Request a new dataset with fewer predictors.
• B. Go back to the data preparation and reduce the number of fields to less than 30 in order to produce a story.
• C. Build the story with all the predictors and indicate that Einstein Discovery should show the top predictors.
• D. Build a story with a first set of predictors and assess which predictors are important to the story. Then drop the less important ones and add the predictors that were omitted in the first run and assess their impact.

Answer: D

Explanation:
Reference:
https://medium.com/@kshannon565/ea-certification-study-guide-part-3-einstein-discovery-story-design-70ffbe4666c2

NEW QUESTION # 83
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