Universal Containers intends to use a custom Salesforce big object in its org and visualize the data using CRM Analytics. As the number of rows to be synced is quite large, the CRM Analytics consultant is looking to set up an incremental sync with additional filters added as part of the data sync to improve performance.
What should the consultant keep in mind while implementing this?

• A. Only SOSL queries can be used as data syne filters.
• B. Custom big objects are NOT supported by CRM Analytics.
• C. Incremental data syne Is NOT supported for big objects.

A consultant is preparing a dataset to predict customer lifetime value and is collecting data from a questionnaire that asks for demographic information. A very small number of respondents fill in the Income box, but the consultant thinks that it is an informative column even though it only represents 1% of respondents.
What should the consultant do?

• A. Apply the predict missing values transformation in recipe nodes.
• B. Fill in the missing data with an average of all incomes.
• C. Drop the field as it will be difficult to get future respondents.

AW Computing will start using Tableau Online to report on some of its Salesforce data to users who do NOT have an SFDC license.
What is the first step the CRM Analytics consultant should take?

• A. Enable the Tableau output connection in the Analytics settings.
• B. Use MuleSoft to generate an API ta connect and push data from SFDC to Tableau.
• C. Select the output connection in the "write to" option of the recipe.

Cloud Kicks needs a CRM Analytics consultant to install the Appointment Analytics App. After installation, they realize the wrong field was picked and the app did not have access to a newly created field that should be used instead of the old one.
What is the first step the consultant should take to prevent erroneous dataset/dashboard creation?

• A. Cancel running installations from Setup
• B. Update the app with the new field after installation.
• C. Stop the recipe from running in Data Manager.

ACRM Analytics consultant is reviewing results from an Einstein Discovery story with a business user. They agree with the findings but notice 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 deploy.
Which action should the consultant take?

• A. Edit the model accuracy settings and rerun it to evaluate the correlation.
• B. A Identify additional data that may have a stronger relationship with the outcome variable.
• C. Use the appropriate algorithm and update the model.