Salesforce CRM Analytics and Einstein Discovery Consultant Practice Exams
Last updated on Oct 22,2026- Exam Code: CRM Analytics and Einstein Discovery Consultant
- Exam Name: Salesforce Certified CRM Analytics and Einstein Discovery Consultant Exam
- Certification Provider: Salesforce
- Latest update: Oct 22,2026
The sales team at Cloud Kicks is requesting that datasets for their dashboards be refreshed every hour. The CRM Analytics consultant investigates if this is possible and finds that the dashboards use five datasets created from two recipes. The first recipe takes 43 minutes to run and the second recipe takes 25 minutes to run.
Which consideration should the consultant keep in mind?
- A . The number of concurrent recipe runs can exceed the limit of two in a 24-hour rolling period.
- B . The total duration of the recipe runtimes can exceed the limit of 1 hour.
- C . The number of concurrent recipe run limits that are associated with the org.
B
Explanation:
In CRM Analytics, recipes are used to prepare and combine data for datasets. The total duration of the recipe runtime is an important consideration when scheduling dataset refreshes. In this case, the combined runtime for both recipes (43 minutes + 25 minutes = 68 minutes) exceeds 1 hour. Since dataset refreshes cannot be scheduled more frequently than the total recipe runtime, it would be impossible to refresh the datasets every hour. This limitation must be considered when managing dataset refresh schedules.
Reference: Recipe runtime limits and considerations for scheduling refreshes are discussed in the CRM Analytics documentation related to recipes and dataflow optimizations.
A model created with a GLM algorithm produced unsatisfactory results.
When re-running the model, which type of algorithm should the consultant use to improve the results?
- A . K-Nearest Neighbors
- B . Support Vector Machines
- C . XGBoost
What is a benefit of introducing a second local connector?
- A . Better maintenance by having a connector per recipe
- B . Better deployment management between sandboxes and production environment
- C . Better performance by syncing data according to the refresh necessities
C
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.
Reference: Best practices for managing connectors and optimizing data sync performance can be found in the CRM Analytics performance optimization guides.
A CRM Analytics consultant is asked to help a company report on its sales activity. The company wants to train some users to create dashboards. The company also wants one other specific team to be able to use the dashboards.
What should the consultant do to address these requirements?
- A . configure a permission set license assignment with two different levels of access.
- B . Clone the existing permission set with different system permissions.
- C . Use a permission set license with two different levels of access.
A
Explanation:
To meet the requirement of training some users to create dashboards while giving another team access to use (but not modify) those dashboards, the best approach is to configure a permission set license assignment with two different levels of access. You can assign specific permissions for dashboard creation to one group of users and viewing permissions to the other. This ensures the appropriate level of access based on the role without the need for duplicating permission sets or licenses unnecessarily.
Reference: The role of permission sets and permission set licenses in managing different levels of access is outlined in Salesforce CRM Analytics user management and security documentation
Cloud Kicks (CK) wants to use CRM Analytics to analyze trends of its sales pipeline in order to accelerate the company’s sales process. To do so, CK needs to know the average time an opportunity spends in each stage. The data can be found in the Opportunity History object, but the value is not pre-calculated in Salesforce, so a consultant recommends using a recipe to calculate it.
How should the consultant use a recipe to calculate the average time an opportunity spends in each stage?
- A . An aggregate transformation with offset parameter to calculate the duration
- B . Flatten transformation with offset expressions to calculate the duration
- C . Custom transformation with a multiple row formula to calculate the duration
A CRM Analytics consultant is building a dashboard for Cloud Kicks that is embedded in a separate Lightning page called "Management Dashboard" using a CRM Analytics Dashboard Component. The system administrator and the contract manager should both have access. The system administrator is able to see the dashboard and the data, but the contract manager sees a blank Lightning page.
What is causing the issue?
- A . The consultant has set up component visibility for the dashboard for system administrators only.
- B . The consultant has set up a dashboard filter condition for data to be visible to system administrators only.
- C . The consultant has set up/enabled a ‘Hide on Error’ feature for the dashboard while embedding it.
A
Explanation:
When embedding a CRM Analytics dashboard in a Lightning page using a CRM Analytics Dashboard Component, you must configure the component’s visibility settings correctly to ensure that all relevant users have access. In this case, the issue arises because the system administrator can see the dashboard, but the contract manager cannot. The most likely cause is that the consultant has set the component visibility to display only for system administrators, which would prevent the contract manager from seeing the content. To resolve this issue, the consultant must modify the component visibility settings to include both the system administrator and contract manager profiles.
Reference: CRM Analytics and Lightning Components
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 a single 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?
- A . Flatten
- B . Custom Multiple row formula
- C . Custom Formula
C
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.
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 . Contact Salesforce Support to increase sync speed.
- C . Enable fast sync in analytics settings.
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.
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 integration user’s currency
- C . In the currency that Is set on the “currency” attribute.
B
Explanation:
When a dataset like "OpportunityDataSet" is populated through a dataflow or recipe in CRM Analytics, the currency values (such as the standard field "Amount") will be displayed in the currency of the integration user unless there is specific currency conversion logic set up within the dataset or recipe. The integration user is the user whose credentials are used to run the dataflow and extract data, and their currency setting will dictate how numeric currency values are displayed unless overridden.
Reference: Salesforce’s documentation on multi-currency environments in CRM Analytics explains how the integration user’s currency affects the display of numeric values.
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 security predicate needs to be updated as ‘Ownerld’ == "sUser.id” || ‘Demography’ = "$User.Demographic__c’.
- C . The Analytics Security User is not provided access permission on custom field Demographic_c on the User object.
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.