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NEW QUESTION 54
A dataset for building the Einstein Discovery story contains 72 fields that are potentially relevant predictors.
Which approach is considered best practice to assess the top predictors in order to get to a meaningful and robust model?
- A. This dataset is too big and cannot be used in Einstein Discovery. Request a new dataset with fewer predictors.
- B. Build the story with all the predictors and indicate that Einstein Discovery should show the top predictors.
- C. Go back to the data preparation and reduce the number of fields to less than 30 in order to produce a story.
- D. Build a story with a first set of predictors and assess which predictors are important to the story. Then drop the less important ones and add the predictors that were omitted in the first run and assess their impact.
Answer: D
Explanation:
Reference:
https://medium.com/@kshannon565/ea-certification-study-guide-part-3-einstein-discovery-story-design-70ffbe4666c2
NEW QUESTION 55
Max of objects that can be enabled for Data Sync
- A. 0
- B. 1
- C. 2
- D. 3
Answer: D
NEW QUESTION 56
Universal Containers (UC) is a multinational company that utilizes Salesforce and has a variety of internal systems. UC uses Einstein Analytics for their data analysis platform and they want to automate their weekly manual process to create a dataset from their on-premise data warehouse. Which solution should a consultant recommend to meet this requirement?
- A. Utilize a Salesforce weekly export feature
- B. Utilize Analytics Connector.
- C. Utilize a dataflow
- D. Utilize middleware with Analytics External Data API
Answer: D
NEW QUESTION 57
The model quality metrics of an Einstein Discovery story indicate that the GINI coefficient in the four folds are 0.82, 0.83, 0.84, and 0.75, respectively.
Which two actions should a consultant take? Choose 2 answers
- A. Research and check the dataset for outliers in the target field and the main predictors that are shown on top of the story.
- B. Confirm that the overall GINI coefficient is good prior to deploying the story.
- C. Do not deploy the story immediately, and research why one fold is performing worse than the others.
- D. Deploy the story, because the variation in the metrics is within the normal range.
Answer: B,C
NEW QUESTION 58
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