Analytics-Con-201 Exam Pattern - Valid Exam Analytics-Con-201 Practice

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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Einstein Discovery	20%	- Describe Einstein Discovery concepts 1. Interpret model results 2. Identify the use cases for Einstein Discovery 3. Explain the model building process - Implement Einstein Discovery 1. Integrate predictions into CRM Analytics dashboards 2. Configure and deploy Einstein Discovery models
Topic 2: Security	10%	- Determine security and sharing settings 1. Describe how Salesforce security is applied in CRM Analytics 2. Implement row-level security
Topic 3: 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 how Salesforce objects map to CRM Analytics 2. Describe use cases for Data Prep (Dataflows and Recipes) 3. Define datasets
Topic 4: Analytics Dashboard Configuration	25%	- Configure dashboards 1. Configure bindings 2. Set up dynamic dashboards 3. Apply query filters
Topic 5: 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

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q106-Q111):

NEW QUESTION # 106
Universal Containers (UC) recently activated data sync in the CRM Analytics data manager. After running the sync, UC notices that the aggregate sum of a field within the company's dataset is different than what they manually calculated by summing the same data in the Salesforce object.
What is causing the issue with the newly synced data?

A. Differences involving flow-updated fields
B. Differences involving formula fields
C. Differences involving trigger-updated fields

Answer: B

NEW QUESTION # 107
The CRM Analytics consultant at Cloud Kicks (CK) notices that a specific dashboard is showing a different date and time from their locale. Upon investigating, they find that the recipe and datasetswere created from a locale with a PST time zone while CK is in the CET time zone.
What led to this problem?

A. The developer turned off dynamic time zone in CRM Analytics settings.
B. Data within datasets is modified for localization or internationalization.
C. The dataset metadata locale Is not overridden by Individual user locale settings.

Answer: A

NEW QUESTION # 108
Cloud Kicks has informed CRM Analytics developers that they have two scenarios with restricted row-level security.
The parameters being:
1. Non-CXOs and VPs working in EMEA can have access to EMEA records only.
2. CXOs and VPs should have access to all data irrespective of the region (APAC, EMEA, etc.).
Which sharing method works for this scenario?

A. Use a field on the user record like Department/Region, and apply row-level security based on that field.
B. Create two sets of dashboards; one for EMEA, and one for CXOs and VPs while filtering the dashboard on the region.
C. Create two separate datasets; one for EMEA, and one for CXOs and VPs.

Answer: A

NEW QUESTION # 109
Cloud Kicks' Salesforce org has multiple currencies enabled. This company's business intelligence team uses CRM Analytics to build a dataflow/recipe that creates a dataset, "OpportunityDataSet", which is populated with data extracted from Opportunity. One of the extracted fields is the standard field, Amount.
Which currency will the Amount values be shown in "OpportunityDataSet"?

A. the connected user's currency
B. In the currency that Is set on the "currency" attribute.
C. In the integration user's currency

Answer: C

NEW QUESTION # 110
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?

A. Bucket transformation in Recipes
B. Detect Sentiment transformation in Recipes
C. Cluster transformation in Recipes

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 # 111
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