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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q38-Q43):

NEW QUESTION # 38
Universal Containers (UC) creates a dataset, "Book11", containing a budget per region per month for the first
6 months of the year, as shown in the graphic below. Now, UC wants to create a lens showing the total budget for each region for each month. Every combination of region and month must be shown in the lens, even if there is no data.

How should a CRM Analytics consultant help UC build this lens?

A. Use a "Compare Table" and use the "Show Totals" option.
B. Use a "fill" statement in SAQL query with a "partition" parameter.
C. Use a "Compare Table" and add a column leveraging the "Running Total" function.

Answer: C

NEW QUESTION # 39
A CRM Analytics consultant has been tasked with providing access to CRM Analytics for a few users. They should be able to view the data but unable to export it.
Which permission should the consultant make sure to NOT include?

A. Download CRM Analytics data
B. Export CRM Analytics data
C. View CRM Analytics Assets

Answer: A

NEW QUESTION # 40
The below image shows a numeric outcome being deployed (Regression).

Which metric is used to calculate the performance of the model in production, specifically in the Model Manager?
The below image shows a numeric outcome being deployed (Regression).
Which metric is used to calculate the performance of the model in production, specifically in the Model Manager?

A. Area Under Curve, Confusion Matrix
B. Root Mean Square Error, Minimum Square Error
C. Area Under Curve, R2 (R-squared)

Answer: B

Explanation:
In the context of a regression model being deployed, the performance metrics used to evaluate its effectiveness in production typically include:
* Root Mean Square Error (RMSE): This metric provides a measure of the average magnitude of the errors between predicted values by the model and the actual values, giving a sense of how accurately the model predicts the outcome.
* Minimum Square Error: While less commonly referenced as "Minimum Square Error", metrics like Mean Squared Error (MSE) are often used to quantify the average of the squares of the errors- essentially, the average squared difference between the estimated values and what is estimated.
These metrics are crucial for assessing the performance of regression models in CRM Analytics, as they directly reflect the accuracy and reliability of the model's predictions in real-world applications.

NEW QUESTION # 41
When deploying a model to an existing Prediction, w number should be considered"1

A. 5: Limit of total number of Prediction Definitions.
B. 20: Limit of number of models under a Prediction Definition.
C. 10: Limit of number of models under a Prediction Definition.
D. 3: Limit of total number of Models.

Answer: C

NEW QUESTION # 42
Universal Containers (UC) is looking to create a dashboard for whitespace analysis. UC wants to view a particular customer and see what similar customers have bought.
Which recipe transformation is helpful for the consultant to use while creating the dataset?

A. Cluster
B. Timeseries Forecasting
C. Predict Missing Values

Answer: A

Explanation:
Cluster transformation is a powerful tool in CRM Analytics recipes used for grouping similar records together based on shared attributes. In this scenario, Universal Containers (UC) wants to perform whitespace analysis by viewing a particular customer and comparing their purchase history with similar customers. The Cluster transformation would help in identifying groups of customers who have made similar purchases. This can then be used to provide insights into what the viewed customer might also be interested in purchasing, based on similar customer behaviors.
Reference: CRM Analytics Recipes and Transformation

NEW QUESTION # 43
......

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