How can you restrict access to Analytics data at the row level?
A. Manually add a flag to each row to prevent access.
B. Use a security predicate to filter which rows are returned.
C. Use subtle thought control.
D. Remove restricted rows from the JSON file.
A Salesforce administrator wants to create a new dashboard that uses custom geoJSON to display data; however, the administrator is unable to upload the file via the UI.
What should be done?
A. Add the system permission "Manage Analytics Custom Maps" to the permission set used.
B. Enable "Custom maps with geoJSON" in the analytics settings.
C. Upload the geoJSON via the API because it is not a function in the UI.
D. Contact Salesforce support and request to get custom maps and geoJSON enabled for the org.
An Einstein Consultant is reviewing the "Why it Happened" Insights provided by Einstein Discovery with the customer. The customer would like to validate the results. Which action should the consultant take?
A. Show the customer how to export and review the R-Code model validation results
B. Check the p-values and standard deviation
C. Use the Share and Export feature to help the customer determine if the findings make logical sense
D. Consult with a Data Scientist to validate the findings
When creating a story in Einstein Discovery, do all potential collinear fields need to be removed before executing the build story'5
A. No. Einstein Discovery is impervious to collinearity, so the story and subsequent model will be fine.
B. No. Although it is ideal to eliminate collinearity as soon as possible, Einstein will give a warning post-build and the ridge regression will prevent collinearity from over-fitting.
C. yes. If all collinear variables are not excluded, the model will over-fit and not make any sense.
D. Yes. If the collinear variables are not removed, the Einstein Discovery model build will fail.
What do you have to assign to users before they can access Analytics?
A. Analytics permission set license (PSL)
B. Permission set with at least one Analytics user permission
C. Username and password
D. A and B
E. B and C
A consultant built a very useful Einstein Analytics app for Sales Operations, and they want to share its contents with the rest of Global Sales. However, they do not want to add everyone in Sales to their app. The consultant recommends extending the Sales Operations app and distributing it as an Einstein
Analytics template app, but needs to locate specific information to get started.
Given the code statement above, which endpoint should it be posted to?
A. /services/data/v##.#/wave/apps
B. /services/data/v##.#/analytics/wizard
C. /services/data/v##.#/analytics/projects
D. /services/data/v##.#/wave/templates
What can you do on the Edit Field Attributes page when uploading a CSV file to Analytics?
A. Change a field's name
B. Change a field's format
C. Change a field's type
D. All of the above
What kind of org should you use for checking challenges when you do Trailhead modules about Analytics?
A. An enterprise org, because that type of org is typically used by large companies
B. A trial org, because you don't need to save anything
C. A Developer Edition org, because it's a free, safe environment where you can try things out
D. A higher education org, because analytics requires advanced math
A company's Salesforce org has multi-currency enabled. This company's business intelligence team used Einstein Analytics to build a dataflow that creates a dataset, "OpportunityDataSet". This dataset is populated with data extracted from the standard object, Opportunity. One of the extracted fields is the standard field, Amount.
If a user explores the "OpportunityDataSet" in Einstein Analytics, in which currency will the Amount values be shown?
A. In the connected user's currency
B. In the integration user's currency
C. In the currency that is set on the "currency" attribute in the dataset
D. In the currency that is set on the "currency" attribute in the dataflow
What are predictive insights good for?
A. Predicting outcomes that you don't actually have the right data for
B. Exploring your existing data to see what already happened
C. Drilling down into the underlying reasons behind a prediction
D. Choosing between all possible outcomes for a single variable