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Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:

1. Which three things can be done with the tableau CRM Dashboard Inspector?
Choose 3 answers

A) See the final query for each query along with query results.
B) View the total time required to run all queries.
C) Automatically remove bottlenecks to make queries run faster.
D) View all queries and the time it took to run each one.
E) Get a list of recommendations on how to improve the performance of the dashboard.

2. Which isn't an option for setting a security predicate for a dataset created from an external data file?

A) In the dataset Security Predicate
B) On each row prior to upload
C) In the metadata file associated with the external data file using the rowLevelSecurityFilter key
D) In the Register transformation node of a dataflow that uses this dataset

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

4. Einstein Discovery is a tool that:

A) Replaces your team of BI experts and data analysts
B) Is like having a personal data scientist on staff
C) Helps you hire the best data scientist for your business
D) Understands your business better than you do

5. 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 "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
B) 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
C) 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
D) 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

Solutions: