Analytics-Con-201 Latest Exam Questions & Analytics-Con-201 Valid Real Exam

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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Weight	Objectives
Data Layer	25%	- Implement and configure the right data transformations 1. Identify and resolve data sync issues 2. Use Data Prep actions - 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
Security	10%	- Determine security and sharing settings 1. Implement row-level security 2. Describe how Salesforce security is applied in CRM Analytics
Einstein Discovery	20%	- Describe Einstein Discovery concepts 1. Identify the use cases for Einstein Discovery 2. Interpret model results 3. Explain the model building process - Implement Einstein Discovery 1. Integrate predictions into CRM Analytics dashboards 2. Configure and deploy Einstein Discovery models
Analytics Dashboard Design	20%	- 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
Analytics Dashboard Configuration	25%	- Configure dashboards 1. Configure bindings 2. Apply query filters 3. Set up dynamic dashboards

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q25-Q30):

NEW QUESTION # 25
What is a benefit of introducing a second local connector?

A. Better deployment management between sandboxes and production environment
B. Better performance by syncing data according to the refresh necessities
C. Better maintenance by having a connector per recipe

Answer: B

Explanation:
Introducing a second local connector in CRM Analytics can improve performance by enabling more granular control over data syncs. By having a separate connector, different datasets or recipes can be synchronized independently based on specific refresh needs, reducing load and improving overall performance. This approach helps optimize data flow operations, especially in large-scale deployments with varying data refresh requirements.

NEW QUESTION # 26

Which timeseries statement will fix the query?

A. q = timeseries q generate 'sum_Sales' as 'Forecasted_Sales' with (dateCols=('Date_Quarter',
'Date_Month', "Q-M"), partition='Region', ignoreLast=true);
B. q = timeserles q generate 'sum_Sales' as 'Forecasted_Sales' with (length=12,dateCols=("Date_Year',
'Date_Month', "Y-M"), partition='Region');
C. q= timeseries q generate 'sum_Sales' as 'Forecasted_Sales' with (dateCols=('Date_Year', 'Date Quarter', "Y-Q"), partition='Region', seasonality=4);

Answer: B

NEW QUESTION # 27
Cloud Kicks has a dashboard that displays accounts and opportunities data in a table that contains actions to open the records in Salesforce. Since the company has allowed several accounts to be created with the same names, when users try to perform actions, they are prompted with only a record ID to select, leaving the users confused and unable to act.
How should the CRM Analytics consultant solve this problem?

A. Insert more fields in the dataset action "Display Fields" so the users know which account they are acting on.
B. Discuss with the stakeholders If the action Is really necessary for the table.
C. Ask the admin to start applying duplicate rules based on the account's Name field.

Answer: A

NEW QUESTION # 28
A team of CRM Analytics developers has been working on an existing recipe to add new derived fields. The edited version has been failing ever since, and management is requesting that the dashboard show refreshed data while they work on the edits.
How can the developers add new fields while keeping the dataset refreshed?

A. Refresh the dataset after working hours to avoid the edited version from failing.
B. Clone the existing recipe to add fields and roll back the original recipe to the last working version.
C. A recipe for the new fields and when that is successful, add it to the existing recipe as a join node.

Answer: B

Explanation:
When faced with the need to continue refreshing data while developing new features in a recipe, the best practice is:
* Clone the Existing Recipe: By cloning the recipe, developers can experiment with adding new fields and transformations without affecting the production data flow. This allows for testing and development in a sandbox-like environment.
* Roll Back to a Stable Version: Rolling back the original recipe to the last stable version ensures that the production dashboards continue to receive refreshed data, maintaining business operations without disruption.
This approach not only ensures data continuity but also provides a safe environment to address any issues that may arise from new developments.

NEW QUESTION # 29
The marketing team at Cloud Kicks has five dashboards in an app. Four widgets are replicas of each other in three of the dashboards.
What is the best way to maintain these widgets?

A. Create/Edit a component for the widgets.
B. Create/Edit the widgets individually on each dashboard.
C. Create/Edit a lens and add each dashboard.

Answer: A

Explanation:
To maintain consistency and ease of updates across multiple dashboards, creating or editing a component for the widgets is the most effective method. This approach:
Efficiency in Updates: Allows changes to be made in one place, which automatically propagates to all instances where the component is used across dashboards.
Consistency: Ensures uniformity in the appearance and functionality of the widgets across different dashboards.
Simplicity: Reduces the need for redundant work, where each widget would otherwise need to be updated individually.

NEW QUESTION # 30
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