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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Analytics Dashboard Configuration	25%	- Configure dashboards 1. Configure bindings 2. Set up dynamic dashboards 3. Apply query filters
Topic 2: Data Layer	25%	- Implement and configure the right data transformations 1. Use Data Prep actions 2. Identify and resolve data sync issues - Identify the right data sources and data flows for CRM Analytics 1. Describe use cases for Data Prep (Dataflows and Recipes) 2. Define datasets 3. Describe how Salesforce objects map to CRM Analytics
Topic 3: Analytics Dashboard Design	20%	- Design and build CRM Analytics dashboards 1. Apply design best practices 2. Use Lenses and Dashboards 3. Describe the use cases for Visualforce and Lightning components
Topic 4: Einstein Discovery	20%	- Implement Einstein Discovery 1. Configure and deploy Einstein Discovery models 2. Integrate predictions into CRM Analytics dashboards - Describe Einstein Discovery concepts 1. Identify the use cases for Einstein Discovery 2. Interpret model results 3. Explain the model building process
Topic 5: Security	10%	- Determine security and sharing settings 1. Implement row-level security 2. Describe how Salesforce security is applied in CRM Analytics

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Analytics-Con-201 Prüfungsfragen mit Lösungen (Q110-Q115):

110. Frage
A consultant is building a CRM Analytics dashboard for Universal
Containers. The consultant has enabled data sync to increase the
speed of datasets refreshing.
How often will the data on the dashboard be refreshed?

A. When the dashboard viewer clicks the Refresh button
B. When dataflow/recipe runs to completion, and then data syne runs to completion
C. When data sync runs to completion, and then dataflow/recipe runs to completion

Antwort: C

111. Frage
Universal Containers (UC) is rolling out CRM Analytics to its field sales that include dashboards withorder data from an external source.
UC has a well-defined role hierarchy where everyone is assigned to an appropriate node on the hierarchy. In addition, the order data has a reference to a Salesforce opportunity.
An individual sales rep should be able to view all orders that they own or as part of the account team or opportunity team. The sales manager should be able to view all orders for the entire sales team. Similarly, the VP of sales should be able to view orders for everyone who rolls up in that hierarchy.
The dataset has a field called Ownerld which represents the order owner.
Given this information, how should a CRM Analytics consultant implement the above requirements?

A. As part of the recipe, use a multi row formula on the Roleld field to create an attribute called
'ParentRoleIDs' on the dataset, and apply the following security predicate:"$User.UserRoleld" ||
'Ownerld' == "$User.Id".
B. As part of the recipe, use the flatten operation on the role hierarchy, create a multi-value attribute called
'ParentRoleIDs' on the dataset, and apply the following security predicate: 'ParentRoleIDs' == "$User.
UserRoleld" || 'TeamMember.Id' '$User, Id" || 'Ownerld' == "$User.Id".
C. As part of the recipe, use a formula on the Roleid fildto create an attribute called 'ParentRolelDs' on the dataset, and apply the following security predicate: 'ParentRolelDs' ==''$UserRoleId'' || Owned\ ==
'$User,id\\,

Antwort: B

Begründung:
In addressing the requirements of Universal Containers to ensure proper visibility of order data across different levels of the sales hierarchy, the use of a security predicate based on role hierarchies is paramount.
Here's why Option B is the ideal approach:
* Flatten Operation on Role Hierarchy: This operation is essential as it allows for the creation of a simplified or "flattened" view of the hierarchical relationships within the organization. This flattened view enables the dataset to understand and respect the hierarchical structure in security implementations.
* Creating a Multi-value Attribute ('ParentRoleIDs'): By creating this attribute, the recipe can hold multiple role IDs that a particular user has visibility permissions for. This is crucial in a hierarchical organization like UC where data visibility needs to cascade down the hierarchy.
* Security Predicate: The predicate ('ParentRoleIDs' == "$User.UserRoleld" || 'TeamMember.Id' ==
'$User.Id' || 'Ownerld' == "$User.Id") effectively enforces that:
* A user can see all orders where their role matches any of the role IDs in the 'ParentRoleIDs' list (hierarchical visibility).
* A user can see all orders where they are specifically listed as a team member.
* A user can see all orders where they are the owner.
This approach aligns with best practices for implementing row-level security in CRM Analytics, ensuring data visibility is managed correctly according to the defined organizational hierarchy and individual data ownership.

112. Frage
A CRM Analytics consultant is performing column profiling on dimension column in a recipe. Newly-added rows are not being considered in the Results tab of theprofile even though a sync wasrun for that specific object.
What is causing the issue?

A. Sync operation has not run properly with the new dimension column in the recipe.
B. Column profiling Is not applicable on a dimension column in a recipe.
C. The sample does not include changes to the connected object data within the last 24 hours.

Antwort: C

113. Frage
A dashboard designer at Cloud Kicks creates a dashboard in CRM Analytics. The designer notices fields display on the dashboard with their APIlabels, such as "AccountId.Industry", and wants to change this behavior.
The designer also notices that the fields and their order appear to randomly change when a values table is created.
What should the CRM Analytics consultant explain to help the designer?

A. The default fields in a values table can be changed by reordering how fields appear in the JSON of the value table.
B. The default fields In a values table and the field labels can be modified in the dataset explorer.
C. The field labels can only be changed in the widget properties in the dashboard edit mode.

Antwort: B

Begründung:
For the scenario at Cloud Kicks where fields display with their API labels and the fields in a values table seem to change order randomly, the correct approach is to modify these settings in the dataset explorer within CRM Analytics. This allows for a more intuitive display and control over how data is presented in dashboards.
Here's how these adjustments help:
* Modifying Field Labels: Changing the field labels from their API names to more user-friendly names enhances readability and user experience. This can be done directly in the dataset explorer, which affects how fields appear across all dashboards utilizing that dataset.
* Controlling Field Order: The order of fields in a values table can seem random if not explicitly set. By using the dataset explorer, a designer can specify the order in which fields appear, which then reflects consistently in the dashboard's values table.
This functionality is part of CRM Analytics' aim to provide flexible and customizable data visualization tools.
Training on these features is available through various Salesforce Trailhead modules that discuss dashboard and dataset customization techniques, providing practical insights and guided tutorials to enhance dashboard design and user interaction.
Both these explanations are consistent with best practices as outlined in Salesforce's CRM Analytics documentation and the Trailhead educational content, ensuring that users are well-equipped to leverage the full capabilities of CRM Analytics for effective data management and presentation.

114. Frage
After getting approval for the dashboard layout design for a desktop, the CRM Analytics consultant is ready to start the design process for a mobile layout.
Which consideration should the consultant keep in mind?

A. Create a layout with the property "phone" to show the dashboard on the mobile app similar to creating a layout with the property "dashboard"to show on the desktop for thesame dashboard,
B. If no layouts are eligible for the mobile device, an error message will be displayed but the dashboard will still be visible on the desktop without errors.
C. "Tablet" or "Phone" layout-where only minWidth and maxWidth have been set-may be displayed on a desktop if the dashboard is embedded in asmall frame, or if the browserwindow is small.

Antwort: C

Begründung:
When designing for different device types in CRM Analytics, particularly for mobile layouts, it's crucial to consider how the layout will respond not just on mobile devices but also under various display conditions on desktops. Here's the rationale for focusing on this consideration:
* Responsiveness: Layouts designated for tablets or phones may also be triggered on desktop environments if conditions such as browser window size or embedded frame dimensions mimic those typical of smaller devices.
* Design Flexibility: Understanding this behavior is essential for creating versatile dashboards that maintain functionality and visual integrity across all potential viewing scenarios.
* User Experience: Ensuring that the dashboard behaves predictably across device types and sizes enhances user engagement and effectiveness, as it provides a consistent experience regardless of the access point.
This approach ensures that the dashboard remains functional and accessible no matter how or where it is being viewed, aligning with best practices for responsive and adaptive design in modern analytics environments.

115. Frage
......

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