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| Section | Weight | Objectives |
|---|---|---|
| Security | 10% | - Determine security and sharing settings
|
| Data Layer | 25% | - Identify the right data sources and data flows for CRM Analytics
|
| Analytics Dashboard Design | 20% | - Design and build CRM Analytics dashboards
|
| Analytics Dashboard Configuration | 25% | - Configure dashboards
|
| Einstein Discovery | 20% | - Implement Einstein Discovery
|
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NEW QUESTION # 31
A consultant runs the sharing inheritance coverage assessment for the Opportunity object and finds that some records exceed 400 sharing descriptors.
What should the consultant do?
Answer: A
Explanation:
When a record exceeds 400 sharing descriptors, it can cause performance issues or sharing rule complications in CRM Analytics. In such cases, the recommended solution is to usesecurity predicates, which allow fine- tuned control over which data is visible to users based on their sharing rules and permissions. Security predicates reduce the number of sharing descriptors by enforcing security at the dataset level rather than relying solely on record-sharing mechanisms.
Increasing the sharing descriptor limit is not an available option, and Salesforce Support does not typically increase this limit, making the use of security predicates the best approach.
Reference:Security predicatesand their use to optimize data visibility and sharing within CRM Analytics are explained in theCRM Analyticsdocumentation related to security and performance.
NEW QUESTION # 32
Universal Containers has a dashboard for sales managers. They need to visualize the percentage of their opportunities in the pipeline in a Gauge chart. They want to customize the chart to keep track if they are below or beyond the target.
Which widget parameters should a consultant use?
Answer: C
Explanation:
In the scenario described, the sales managers at Universal Containers require a Gauge chart that not only shows the current percentage of opportunities in their pipeline but also indicates whether they arebelow or beyond their set targets. The appropriate widget parameters to achieve this visualization in Salesforce CRM Analytics (formerly known as Einstein Analytics) are:
* Reference Line: This parameter is crucial for defining a specific target value on the gauge chart. It visually marks a point that represents the target goal, providing an immediate visual cue as to whether the current percentage is below or above this point.
* Markers: Markers are used to represent and highlight specific values on the gauge chart. They can be utilized to emphasize the current percentage level of the pipeline, making it instantly visible how close or far the current value is from the reference line or target.
* Conditional Formatting: This feature allows the chart to change color or style based on whether the current values meet, exceed, or fall below the target. It is a critical visual tool for quickly communicating performance against targets. Conditional formatting can be set to alter the appearance of the gauge's fill color based on whether the values are above, equal to, or below the reference line, thereby providing an intuitive visual representation of performance relative to targets.
The combination of these three parameters enables a highly effective visualization for sales managers to monitor their performance against key metrics and targets directly on their dashboards. This setup is aligned with Salesforce's best practices for creating meaningful and actionable insights within CRM dashboards, ensuring that users can easily interpret and react to the data presented.
For more details on configuring these parameters, you can refer to Salesforce documentation and specific Trailhead modules that cover dashboard creation and customization:
* Wave Analytics Explorer
* Building Lenses, Dashboards, and Apps in CRM Analytics
These resources provide in-depth training and examples to help users effectively use Salesforce CRM Analytics for a wide range of data visualization needs.
NEW QUESTION # 33
ACRM Analytics consultant is reviewing results from an Einstein Discovery story with a business user. They agree with the findings but notice that none of the fields used in the story have a correlation value greater than
4%. The client is now concerned that the model
may not be good enough to deploy.
Which action should the consultant take?
Answer: C
NEW QUESTION # 34
Universal Containers' sales team is looking to build a dashboard that shows the total revenue from their top
10 accounts (based on revenue) and make it dynamic with the filters of the dashboard.
Which action is required to accomplish this?
Answer: B
Explanation:
To create a dashboard showing the top 10 accounts by revenue dynamically, the best approach is to create a query that sorts the accounts in descending order by revenue and limits the results to the top 10. This query can then be used as the data source for the widget, ensuring that it dynamically adjusts based on the filters applied to the dashboard.
This method efficiently handles the task because sorting by revenue and limiting the results to 10 ensures that only the top accounts are displayed, and it remains dynamic with dashboard filters.
NEW QUESTION # 35
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: C
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 # 36
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