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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q15-Q20):NEW QUESTION # 15
Universal Containers asks a CRM Analytics consultant to review the performance of its local data sync.
After removing unused objects and fields from connected data, what else should the consultant do to improve performance of the data sync?
- A. Evaluate connection mode for each connected object.
- B. Enable fast sync in analytics settings.
- C. Contact Salesforce Support to increase sync speed.
Answer: A
Explanation:
To improve the performance of local data sync in Universal Containers, evaluating the connection mode for each connected object is a practical approach. Here's the rationale:
* Optimization of Resources: Different connection modes (e.g., Full Sync, Incremental Sync) use different amounts of resources. Choosing the right mode for each object based on how frequently its data changes can optimize the sync process and reduce load times.
* Efficient Data Handling: By tailoring the connection mode to the needs of specific data objects, the overall efficiency of the data sync process is improved, leading to faster refresh rates and more timely data availability.
* Cost and Performance Balance: Evaluating and selecting the appropriate connection mode can also help balance performance needs with cost constraints, as some modes may consume more compute resources than others.
NEW QUESTION # 16

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 # 17
A client has two datasets that are used across seven different dashboards. Three of these dashboards are used by marketing and four are used by sales. The client requires that only marketing can access the marketing dashboards and only sales can access the sales dashboards.
Which solution should a consultant recommend?
- A. Create three custom apps: one for marketing dashboards with marketing as "viewer", one for sales dashboards with sales as "viewer", and one for datasets where marketing and sales are "viewer".
- B. Use two custom apps: one for marketing dashboards with marketing as "viewer" and one for sales dashboards with sales as "viewer". Add the datasets as references to both custom apps.
- C. Duplicate the datasets and create two custom apps: one for marketing dashboards and datasets with marketing as "editor" and one for sales dashboards and datasets with sales as "editor".
Answer: A
NEW QUESTION # 18
Cloud Kicks (CK) has a dashboard in CRM Analytics with forecasting data. One widget is a compare table using the timeseries function showing the quarterly forecast. However, CK is interested in enhancing the dashboard with a weekly forecast per customer.
How should CK achieve this?
- A. An SAQL query with a timeseries statement specifying Opportunity Name as the partition and Y-M-W as the Date Cols
- B. An SAQL query with @ timeseries statement specifying Account Name as the partition and Y-M-D as the Date Cols
- C. An SAQL query with a timeseries statement specifying Account Name as the partition and Y-M-W as the Date Cols
Answer: C
Explanation:
To create a weekly forecast per customer, anSAQL (Salesforce Analytics Query Language)query can be used.
The timeseries function generates forecast data based on a specified date range. In this case, the forecast is customer-specific, meaning the partition should be based onAccount Nameto ensure that the forecast is generated for each customer. The date column (Date Cols) should be set to Y-M-W to aggregate the forecast data on a weekly basis.
NEW QUESTION # 19
Universal Containers has a well-defined role hierarchy in Salesforce where everyone is assigned to an appropriate node. The accounts within their instance are categorized by their demography.
An individual sales rep should be able to view all accounts that they own. In addition, sales reps should be able to see any accounts where the value of the account demography matches the demography defined on their user record. A user could have more than one demography defined on their user record.
To meet this requirement, the CRM Analytics consultant has set up a security predicate of the existing
'Account' dataset as follows:

This, however, does not seem to be working as expected.
What is causing the issue?
- A. The Sales Rep is not provided access permission on custom field Demographic__c on the User object.
- B. The Analytics Security User is not provided access permission on custom field Demographic_c on the User object.
- C. The security predicate needs to be updated as 'Ownerld' == "sUser.id" || 'Demography' = "$User.
Demographic__c'.
Answer: A
Explanation:
The issue with the security predicate not functioning as expected likely stems from a permissions issue related to the custom field Demographic__c on the User object. Here's a detailed explanation:
* Field-Level Security: If the sales reps do not have access to the Demographic__c field, the security predicate which references this field cannot execute properly as the system cannot evaluate the predicate without accessing the field.
* Permission Settings: Ensuring that the sales reps have the necessary permissions to view and use the Demographic__c field is crucial for the security predicate to function correctly.
* Data Visibility: The security model in CRM Analytics relies heavily on the underlying data permissions in Salesforce. If these permissions are not correctly configured, the expected data visibility through CRM Analytics will not be achieved.
NEW QUESTION # 20
......
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