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Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:

1. The Einstein Analytics Plus Platform license is enabled for a Salesforce org and assigned to each user. However, these users cannot see the Einstein Analytics Studio in the App Launcher.
How can this issue be addressed?

A) Share the app with the users in Einstein Analytics.
B) Create user accounts for the users in Einstein Analytics.
C) Assign the users to the permission set containing Use Analytics.
D) Assign the users to the permission set containing Manage Analytics.

2. As a tableau CRM consultant you have been asked to bring data from a Snowflake database as well external Salesforce environment into Tableau CRM (CRM Analytics Plus edition). 25 objects have been enabled from the local Salesforce connector. After further investigation of the external Salesforce environment and 15 object each from the remaining 2 external Salesforce environment. You estimate each connector will per object bring between 1000 and 1 mil rows of data.
What limit will be exceeded?

A) Snowflake connector number synced rows
B) Salesforce external connector number of synced rows
C) Storage rows of data
D) Total number of enabled objects

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

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

4. What is the order of filter, limit, order and offset functions in SAQL?

5. Results from an Einstein Discovary story are reviewed with a business user. They agree with the findings but noticed that none of the fields used in the story have a correlation value greater than 4%. The client is now concerned that the model may not be good enough to next steps?

A) Identify additional data that may have a stronger relationship with the outcome variable.
B) Rerun and update the story with a different algorithm.
C) Edit the model accuracy settings and rerun the story.
D) Proceed with deployment if the model quality metric values ire sufficient.

Solutions: