A company wants to use Einstein Analytics to analyze the trend of their sales pipeline. The company wants to accelerate the sales process. To do so, they need to know the average time an opportunity spends in each stage. This value is not pre-calculated in Salesforce, so a consultant recommends using a dataflow to calculate it.
How can a dataflow be used to calculate the average time an opportunity spends in each stage?

• A. computeExpression Transformation with SAQL Expression to calculate the duration
• B. flatten Transformation with Offset Expressions to calculate the duration
• C. computeRelative Transformation with offset parameter to calculate the duration
• D. computeRelative Transformation with SAQL Expression to calculate the duration

In what order does Einstein Discovery present the insights that it uncovers?

• A. Insights that explain the most variation in the outcome variable, in descending order
• B. B and D
• C. Insights that explain the most variation in the outcome variable, in ascending order
• D. Alphabetical, in ascending order
• E. Alphabetical, in descending order

After getting approval of the dashboard layout design for a desktop, the Einstein Analytics consultant is ready to start the design process for a mobile layout.
What are three considerations that the consultant should keep in mind when developing the layout? Choose 3 answers

• A. If more than one layout is eligible, the one with the most device properties set is used. If there is a tie, the most recently defined layout is used. (Missed)
• B. If no layouts are eligible for the mobile device, an error message will be displayed.
• C. If no layouts are eligible for the mobile device, the first defined layout is used. (Missed)
• D. A layout for mobile is eligible for use when the device meets all the device properties set in the Layout panel.
• E. There are widgets that cannot be displayed on mobile layouts.

In Einstein Analytics, which node is used in a dataflow to extract data from a registered dataset?

• A. edgemart
• B. export
• C. digest
• D. sfdcDigest

A customer is reviewing a story that is set to maximize the daily sales quantity of consumer products in stores and sees this chart. The visualized tooltip belongs to the blue bar for San Francisco, reflecting, November daily sales quantities in that city specifically.
What two conclusions can be drawn from this insight?

• A. The average daily in SAN Francisco stores in November as 1601 items higher than the global average of 335.
• B. November sales are higher than in other months. This November-effect is the strongest in San Francisco.
• C. The average daily quantity in San Francisco stores in November was 1239 items higher than the average of all November sales in the country
• D. The average daily quantity in San Francisco stores in November was 1239 items higher than the average of all other months in San Francisco.