Analytics-Con-201 Valid Exam Bootcamp, Exam Analytics-Con-201 Vce

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Salesforce Analytics-Con-201 Exam Syllabus Topics:

SectionWeightObjectives
Data Layer25%- 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. Describe how Salesforce objects map to CRM Analytics
  • 3. Define datasets
Analytics Dashboard Design20%- Design and build CRM Analytics dashboards
  • 1. Use Lenses and Dashboards
  • 2. Apply design best practices
  • 3. Describe the use cases for Visualforce and Lightning components
Security10%- Determine security and sharing settings
  • 1. Implement row-level security
  • 2. Describe how Salesforce security is applied in CRM Analytics
Analytics Dashboard Configuration25%- Configure dashboards
  • 1. Configure bindings
  • 2. Apply query filters
  • 3. Set up dynamic dashboards
Einstein Discovery20%- Implement Einstein Discovery
  • 1. Integrate predictions into CRM Analytics dashboards
  • 2. Configure and deploy Einstein Discovery models
- Describe Einstein Discovery concepts
  • 1. Identify the use cases for Einstein Discovery
  • 2. Explain the model building process
  • 3. Interpret model results

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q67-Q72):

NEW QUESTION # 67
An CRM Analytics consultant is working with Ursa Major Solar to build a dashboard to understand customer renewals. Each subscription is captured as a Closed Won Opportunity within Salesforce and asingle Account should only have one active subscription. The consultant notices the Opportunity record does NOT specify whether it is a renewal or a net new subscription.
Which data transformation should the consultant use to determine if a subscription is new or a renewal?

Answer: B

Explanation:
To determine whether a subscription is new or a renewal from the Opportunity records in Salesforce, the consultant should utilize a Custom Formula in the data transformation process. Here's the rationale:
* Custom Formula Usage: By employing a custom formula, the consultant can create a logical expression that checks the historical data associated with each account. If an account has previous closed-won opportunities, any new opportunities can be labeled as renewals; otherwise, they are considered new subscriptions.
* Data Insight: This method provides a straightforward way to derive new insights (new vs. renewal) directly from existing data without altering the data structure itself, making it a non-invasive and efficient solution.
* Implementation: The custom formula can be applied in a recipe or directly within a dataflow in CRM Analytics, offering flexibility in how and where the transformation is executed.


NEW QUESTION # 68
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 # 69
Cloud Kicks uses CRM Analytics for its sales reporting. A new manager needs access to CRM Analytics to see specific dashboards.
How should the system administrator give access to the Analytics
Studio app in the App Launcher?

Answer: A


NEW QUESTION # 70
In Data Alerts, a field named Region is 96.5% North America. The consultant believes that this is an important field since the majority of sales is in the North American market.
What is the appropriate action?

Answer: C


NEW QUESTION # 71
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: C

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 # 72
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