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| Section | Objectives |
|---|---|
| Topic 1: Security and Access | - Row-level security and sharing rules - App and dataset permissions |
| Topic 2: Dashboard and App Development | - Interactive filters and user experience optimization - Lens creation and dashboard design |
| Topic 3: Data Integration and Connectivity | - Data synchronization and refresh strategies - Connecting external data sources |
| Topic 4: Data Management and Preparation | - Dataset creation and configuration in CRM Analytics - Data transformation and dataflows |
| Topic 5: Einstein Discovery | - Insights interpretation and recommendations - Model building and predictions |
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NEW QUESTION # 10
A CRM Analytics consultant has enabled data sync manually in an org that uses dataflows/recipes. The client says that the dataflow/recipe fails each time it starts running.
What is causing the dataflow/recipe to fail?
Answer: A
NEW QUESTION # 11
A CRM Analytics consultant has been asked to bring data from an external database as well as five external Salesforce environments into CRMAnalytics. Twenty-five objects have been enabled from the local Salesforce connector.
The requirements are:
* 10 objects should be enabled from an external database
* 12 objects each from three of the external Salesforce environments
* 15 objects each from the remaining two external Salesforce environments The consultant estimates each connector will, per object, bring between 1,000 and 1 million rows of data.
Which limit will be exceeded?
Answer: B
Explanation:
In evaluating the scenario presented where multiple external sources and objects are being integrated into CRM Analytics, we need to consider the total number of enabled objects across all connections. Here's a breakdown:
* 10 objects from an external database
* 12 objects each from three external Salesforce environments, totaling 36 objects
* 15 objects each from two external Salesforce environments, totaling 30 objects
* 25 objects already enabled from the local Salesforce connector
This brings us to a total of 101 objects enabled, which may exceed typical limits on the number of objects that can be enabled in a CRM Analytics environment, depending on the specific Salesforce licensing and platform limits.
NEW QUESTION # 12
Universal Containers (UC) has a "Sales Manager" dashboard. UC has a compare table that has multiple groupings and columns added showing the Total and Subtotals of the numeric values. A consultant is asked to add additional groups to enhance details about UC's customers.
Which feature should the consultant use to make the navigation of the compare tables easier for the end user?
Answer: C
NEW QUESTION # 13
A CRM Analytics consultant is asked to help a company report on its sales activity. The company wants to train some users to create dashboards. The company also wants one other specific team to be able to use the dashboards.
What should the consultant do to address these requirements?
Answer: B
Explanation:
To meet the requirement of training some users to create dashboards while giving another team access to use (but not modify) those dashboards, the best approach is to configure a permission set license assignment with two different levels of access. You can assign specific permissions for dashboard creation to one group of users and viewing permissions to the other. This ensures the appropriate level of access based on the role without the need for duplicating permission sets or licenses unnecessarily.
NEW QUESTION # 14
A company realizes it has a lot of rich information around its cases, but unfortunately, most of this isunstructured/textual data. Thecompany is exploring how to include some of this information in its case prioritization.
Which option within CRM Analytics should a consultant leverage?
Answer: B
Explanation:
For a company with a wealth of unstructured textual data in their cases, the "Detect Sentiment" transformation within CRM Analytics Recipes is a crucial tool. This transformation analyzes the sentiment of the text data- whether it's positive, neutral, or negative-and this insight can be highly valuable in case prioritization processes. Here's why this transformation is useful:
* Insight into Customer Sentiments: By detecting sentiment, the company can prioritize cases based on the urgency and emotional tone expressed in the text, which might indicate customer dissatisfaction or urgency.
* Automation and Efficiency: Automatically categorizing cases based on sentiment can streamline workflows and ensure that critical cases are handled promptly.
* Enhanced Customer Service: Responding to negative sentiments swiftly can improve customer satisfaction and potentially mitigate issues before they escalate.
NEW QUESTION # 15
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