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Salesforce Implement and Manage Tableau CRM Sample Questions (Q92-Q97):

NEW QUESTION # 92
The client is trying to create a SAQL step to predict sales in each sales region. They cannot get the query to return any results, but have identified that the error is in the time series statement. They have asked an Einstein Consultant to review the following query and fix any errors.

Which timeseries statement will fix the query'

A. q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (Iength = 12, dateCols=('Date_Year', 'Date_Month". "Y-M"), partition='Region');
B. q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', "Y-Q"), partition='Region');
C. q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', "Y-Q"), partition='Region', seasonality=4);
D. q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (dateCols=('Date_Year, Date_Quarter', "Y-Q"), partition=Region', ignoreLast=true);

Answer: A

NEW QUESTION # 93
Which of these is not a method for controlling record-level access?

A. Role Hierarchy
B. Sharing Rules
C. Organization-Wide Defaults
D. Profiles

Answer: D

Explanation:
https://help.salesforce.com/articleView?id=bi_security_datasets_row_level.htm
https://help.salesforce.com/articleView?id=managing_the_sharing_model.htm&type=5

NEW QUESTION # 94
In a story investigating margin, large variations between product groups are dominating the story. Which action might an Einstein Consultant take to resolve this?

A. Normalize the margin by product group.
B. Eliminate extreme values in the dataset.
C. Add more data to the dataset.
D. Run separate stories for each region.

Answer: B

NEW QUESTION # 95
In Einstein Analytics, which node is used in a dataflow to extract data from a registered dataset?

A. sfdcDigest
B. export
C. digest
D. edgemart

Answer: D

NEW QUESTION # 96
When creating a story in Einstein Discovery, do all potential collinear fields need to be removed before executing the build story'5

A. No. Although it is ideal to eliminate collinearity as soon as possible, Einstein will give a warning post-build and the ridge regression will prevent collinearity from over-fitting.
B. yes. If all collinear variables are not excluded, the model will over-fit and not make any sense.
C. Yes. If the collinear variables are not removed, the Einstein Discovery model build will fail.
D. No. Einstein Discovery is impervious to collinearity, so the story and subsequent model will be fine.

Answer: A

NEW QUESTION # 97
......

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Hugh Tate Hugh Tate

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Salesforce Implement and Manage Tableau CRM Sample Questions (Q92-Q97):