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Salesforce Implement and Manage Tableau CRM Sample Questions (Q160-Q165):
NEW QUESTION # 160
What are predictive insights good for?
- A. Choosing between all possible outcomes for a single variable
- B. Predicting outcomes that you don't actually have the right data for
- C. Drilling down into the underlying reasons behind a prediction
- D. Exploring your existing data to see what already happened
NEW QUESTION # 161
An insurance company has many Einstein Analytics dashboards that show the influence of weather, such as atmospheric temperature, on customer cases. A service agent commented that it is sometimes difficult to determine, by looking at a dashboard, whether the temperature data is reported in degrees Fahrenheit or in degrees Celsius.
How can a dashboard designer ensure the temperature data is easier to interpret on the dashboards?
- A. In Explorer, go to the Fields menu and then customize the number format of the measure.
- B. Customize the number format in the number widget properties of the dashboard.
- C. Add a text widget to the dashboard to indicate Fahrenheit or Celsius.
- D. Use the XMD node in the dataflow to customize the number format of the field.
NEW QUESTION # 162
A customer wants to change the default blue color on a bar chart. What is the easiest way to change blue to another color?
- A. Create a compare table formula to specify a hidden metric for coloring purposes.
- B. Use conditional formatting under the bar chart widget properties by selecting the dimension.
- C. Use bindings to specify a color per bar.
- D. Use conditional formatting under the bar chart widget properties by selecting the measure.
NEW QUESTION # 163
Upper and lower limits on columns (vars) in discovery:
- A. 20 column minimum, 50 maximum
- B. 10 column minimum, 200 maximum
- C. 2 column minimum, 25 maximum
- D. 2 column minimum, 50 maximum
NEW QUESTION # 164
An Einstein Analytics team wants to create a dashboard using two standard Salesforce objects. The dashboard should display data from the Case object, along with related data from the Account object. Which two processes can achieve this?
- A. Extract data from the case and account objects using "sfdcDigest" transformation, y/ Q use "augment" transformation to add case data with account data, store as a dataset, and then build a dashboard using the generated dataset
- B. Extract data from the case and account objects using "dataloader", create a CSV file Q with account and case data, and then upload the CSV as a dataset to Einstein Analytics. Build a dashboard using that dataset
- C. Extract data from the case and account objects using "sfdcDigest" transformation, Q use "append" transformation to add case data with account data, store as a dataset, and then build a dashboard using the generated dataset
- D. Extract data from the case and account objects using an ETL tool, use the ETL tool to y/ Q join account and case data, and then upload the data to Einstein Analytics. Build a dashboard using the ETL generated dataset
NEW QUESTION # 165
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