Analytics-Con-201 Exam Questions & Answers
Salesforce Certified CRM Analytics and Einstein Discovery Consultant • Salesforce
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Sample Analytics-Con-201 Questions
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A versioning feature allows CRM Analytics users to be added as Publishers and make changes separately while a 'Live' version is still being usedby other users. Once the changes are complete, the user can then set their updated version as the Live version.
Which CRM Analytics item is this leveraged for?
In CRM Analytics, the versioning feature described is typically leveraged for Apps. This feature allows:
Parallel Development: Users can work on changes in a separate version without affecting the live version being accessed by others.
Controlled Publishing: Once changes are finalized, the user can then promote their version to be the new live version, ensuring seamless updates without disrupting ongoing usage.
Collaborative Workflows: Facilitates teamwork by allowing multiple users to propose and test changes in a controlled environment before making those changes live.
This approach ensures that CRM Analytics apps remain dynamic and can evolve over time while maintaining stability and continuity for end-users.
Universal Containers plans to upload target data from an external tool to CRM Analytics so it can calculate the sales team target attainments.
The target data changes every month, so the datasets need to be updated on a monthly basis. The target data is a CSV file that contains the Salesforce ID of the sales rep, the target amount, and the month of the target. For each sales rep, the file contains a target for every month of the current year as well as all previous years.
Based on this information, which operation should a consultant use with the Analytics External Data API to upload the file?
For uploading target data that changes on a monthly basis and includes historical data (previous years' targets), the appropriate operation is "Overwrite." This ensures that each time the CSV file is uploaded, the existing data in the dataset is replaced with the new data. This is critical because the target data includes both current and historical data, and using "Overwrite" will update the entire dataset while maintaining historical accuracy.
"Append" would add new data without replacing the old records, leading to duplication, and "Update" is not suitable for completely replacing data in this context.
What is a benefit of introducing a second local connector?
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.
A data architect wants to use a recipe transformation to implement row level security based on role hierarchy in Salesforce.
Which transformation should the architect use to level the dataset hierarchy?
A CRM Analytics consultant has been asked to add a custom object to existing recipe. When trying to locate the object, the consultant can see only Direct Data and NOT the SFDC Local data sync.
How should the consultant resolve this?
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