When organizing information in an Einstein Analytics dashboard, what does the "Progressive Disclosure' design principle mean'

• A.Intentionally omit specific details so that users can do ad-hoc exploration if needed for root-cause analysis.
• B.Only provide the user with the level of detail they need to see, with the option to drill down deeper into more details.
• C.Utilize the latest templates for the most modern look and feel.
• D.Implement strict security predicates to minimize the amount of information displayed to users.

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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.

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How many external files can be uploaded to Einstein Analytics on rolling 24 hour basis?

• A.500 files per dataset
• B.100 files per dataset
• C.50 files Per dataset
• D.300 files per dataset

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

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The Universal Containers company used Einstein Analytics to create two datasets:
Dataset A: contains a list of activities with an "activitylD" dimension and a "userlD" dimension Dataset B: contains a list of users with a "userlD" dimension The team wants to delete from Dataset A all activities related to users in Dataset B.
How can an Einstein Consultant help them achieve this?

• A.Use the dataflow transformation "delete" and set "userlD" as the deletion ID.
• B.Use a combination of dataflow transformations: "augment" and "filter."
• C.Use an external ETL tool to extract both datasets and delete records.

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