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| Section | Weight | Objectives |
|---|---|---|
| Analytics Dashboard Design | 20% | - Design and build CRM Analytics dashboards
|
| Data Layer | 25% | - Identify the right data sources and data flows for CRM Analytics
|
| Analytics Dashboard Configuration | 25% | - Configure dashboards
|
| Einstein Discovery | 20% | - Implement Einstein Discovery
|
| Security | 10% | - Determine security and sharing settings
|
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NEW QUESTION # 73
What is a benefit of introducing a second local connector?
Answer: C
Explanation:
Introducing a second local connector in CRM Analytics can improve performance by enabling more granular control over data syncs. By having a separate connector, different datasets or recipes can be synchronized independently based on specific refresh needs, reducing load and improving overall performance. This approach helps optimize data flow operations, especially in large-scale deployments with varying data refresh requirements.
NEW QUESTION # 74
Exhibit.
Universal Containers has a dashboard for sales managers to visualize the Year Over Year (YoY) growth of their customers. The formula used is:
YoY = [(This Year - Last Year) / Last Year] %
Based on the graphic, when there is not an account in the Last Year column, the YoY Growth shows null results. The sales managers want to replace it with 100% value.
What is the correct function to use?
Answer: A
NEW QUESTION # 75
A versioning feature allows CRM Analytics users to be added as Publishers and make changes separately while a 'Live' version is still being usedby other users. Once the changes are complete, the user can then set their updated version as the Live version.
Which CRM Analytics item is this leveraged for?
Answer: A
Explanation:
In CRM Analytics, the versioning feature described is typically leveraged for Apps. This feature allows:
* Parallel Development: Users can work on changes in a separate version without affecting the live version being accessed by others.
* Controlled Publishing: Once changes are finalized, the user can then promote their version to be the new live version, ensuring seamless updates without disrupting ongoing usage.
* Collaborative Workflows: Facilitates teamwork by allowing multiple users to propose and test changes in a controlled environment before making those changes live.
This approach ensures that CRM Analytics apps remain dynamic and can evolve over time while maintaining stability and continuity for end-users.
NEW QUESTION # 76
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?
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 # 77
Universal Containers' CRM Analytics team is building a dashboard with two widgets.
1. List widget associated to the query "Type_2" and grouped by the dimension "Type" (multi-selection)
2. Donut chart widget associated to the query "Step_pie_3" and grouped by the dimension "Type" The team wants to use bindings/interactions so any selection in the List widget will filter the Donut chart. The queries use different datasets, and users should be able to choose more than one Type (multi-selection).
What is the right syntax for the binding/interaction?
Answer: A
Explanation:
For the given requirement where a selection in a list widget needs to filter data displayed on a donut chart, and considering the list allows for multi-selection of the 'Type', the correct binding/interaction would be to use a syntax that captures the multi-select aspect and passes it appropriately. The right syntax, as indicated in Option A, looks like this:
"{{column(Type_2.selection, [\"Type\"]).asObject()}}"
This syntax ensures:
* Multi-selection: The column() function in combination with .asObject() ensures that multiple selected values from the 'Type_2' query can be passed as an object, which the donut chart can utilize to filter its content.
* Correct Data Type Handling: By using .asObject(), the binding ensures the data passed between widgets maintains the correct structure expected by the CRM Analytics dashboard, thereby ensuring accurate filtering.
NEW QUESTION # 78
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