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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Exam Syllabus Topics:

Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:

1. Why is it important to prepare the data in a CSV file before you bring it into Analytics?

A) To add currency symbols to numeric fields
B) To make sure the content is interesting
C) To make sure Analytics can set the field type correctly
D) To remove column headers

2. How can you restrict access to Analytics data at the row level?

A) Use a security predicate to filter which rows are returned.
B) Use subtle thought control.
C) Manually add a flag to each row to prevent access.
D) Remove restricted rows from the JSON file.

3. What does XMD stand for?

A) Lenses Dataset Fields
B) Extended Metadata
C) Create a JSON
D) Configuring unsupported fields

4. What's the best way to describe the template-info.json file?

A) It's automatically populated every time you create an app from the template.
B) It makes sure that the app includes all the right Salesforce data.
C) It's the boss of the template with all the information needed to create the app.
D) It's a read-only file with all the user documentation for a template.

5. The client is trying to create a SAQL step to predict sales in each sales region. They cannot get the query to return any results, but have identified that the error is in the time series statement. They have asked an Einstein Consultant to review the following query and fix any errors.

Which timeseries statement will fix the query'

A) q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (dateCols=('Date_Year, Date_Quarter', "Y-Q"), partition=Region', ignoreLast=true);
B) q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', "Y-Q"), partition='Region', seasonality=4);
C) q = timeseries q generate 'sum_Sales' as Forecasted_Sales' with (Iength = 12, dateCols=('Date_Year', 'Date_Month". "Y-M"), partition='Region');
D) q = timeseries q generate 'sum_Sales' as Torecasted_Sales' with (dateCols=('Date_Year', Date_Quarter', "Y-Q"), partition='Region');

Solutions: