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Quiz Trustable CRM-Analytics-and-Einstein-Discovery-Consultant - Simulated Salesforce Certified CRM Analytics and Einstein Discovery Consultant Test
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| Topic |
Details |
| Topic 1 |
- Einstein Discovery: This section unveils the magic of AI-driven insights and candidates' ability to analyze and choose one of the three types of predictions. It involves leveraging Einstein's advanced analytics capabilities to adjust data parameters, add or remove data and columns for the improvement of the model.
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| Topic 2 |
- Analytics Dashboard Design: Building upon the design foundation, this section challenges candidates to bring their dashboard designs to life. It covers the technical expertise required to scope, validate, and prioritize dashboard design requirements.
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| Topic 3 |
- Admin
- Configuration: This topic takes Salesforce consultants on a journey through the enablement of CRM Analytics. It tests their ability to design a solution that is suitable for data sync
- dataflows
- recipe limits.
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Visual CRM-Analytics-and-Einstein-Discovery-Consultant Cert Exam - Latest CRM-Analytics-and-Einstein-Discovery-Consultant Test Notes
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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q69-Q74):
NEW QUESTION # 69
The Universal Containers company used Einstein Analytics to create two datasets:
Dataset A: contains a list of activities with an "activitylD" dimension and a "userlD" dimension Dataset B: contains a list of users with a "userlD" dimension The team wants to delete from Dataset A all activities related to users in Dataset B.
How can an Einstein Consultant help them achieve this?
- A. Use a combination of dataflow transformations: "augment" and "filter."
- B. Use the dataflow transformation "delete" and set "userlD" as the deletion ID.
- C. Use an external ETL tool to extract both datasets and delete records.
Answer: A
Explanation:
D, Use the recipe operation "delete" and set "userlD" as the deletion ID.
NEW QUESTION # 70
Universal Containers (UC) is looking to create a dashboard for whitespace analysis. UC wants to view a particularcustomer and see what similarcustomers have bought.
Which recipe transformation is helpful for the consultant to use while creating the dataset?
- A. Timeseries Forecasting
- B. Cluster
- C. Predict Missing Values
Answer: B
NEW QUESTION # 71
Which statement best describes how to ensure Einstein Analytics dashboards are easily used across both desktop and mobile devices?
- A. Create multiple layouts, ensure the layout selectors match the device, and resize/hide widgets as necessary to ensure the content is appropriate for the device screen size.
- B. Create a single layout and allow Einstein Analytics to automatically organize dashboard contents to be optimal for the device type.
- C. Create multiple layouts, and reorder all the widgets so that they fit nicely within the new default width.
- D. Create a single layout and reorder all the widgets so that they fit nicely when viewing on either device.
Answer: A
NEW QUESTION # 72
Cloud Kicks (CK) has a dashboard in CRM Analytics with forecasting data. One widget is a compare table using the timeseries function showing the quarterly forecast. However, CK is interested in enhancing the dashboard with a weekly forecast per customer.
How should CK achieve this?
- A. An SAQL query with a timeseries statement specifying Account Name as the partition and Y-M-W as the Date Cols
- B. An SAQL query with @ timeseries statement specifying Account Name as the partition and Y-M-D as the Date Cols
- C. An SAQL query with a timeseries statement specifying Opportunity Name as the partition and Y-M-W as the Date Cols
Answer: A
Explanation:
To create a weekly forecast per customer, anSAQL (Salesforce Analytics Query Language)query can be used.
The timeseries function generates forecast data based on a specified date range. In this case, the forecast is customer-specific, meaning the partition should be based onAccount Nameto ensure that the forecast is generated for each customer. The date column (Date Cols) should be set to Y-M-W to aggregate the forecast data on a weekly basis.
NEW QUESTION # 73
A company used Einstein Analytics to create two datasets:
1. "Opportunity With Account- dataset, which contains data from the Opportunity standard object augmented by the Account data.
2. "Case with Account" dataset. which contains data from the Case standard object augmented by the Account data.
The company wants to build a lens showing the total number of Opportunities and Cases per Account. How can a consultant help them build this lens'
- A. Create a recipe to generate a new dataset from the "OpportunityWithAccount" and "CaseWithAccount" datasets aggregated by Account, and use the generated dataset in a lens.
- B. Use "Compare Table" to join the "OpportunityWithAccount" and "CaseWithAccount" datasets using the "Accountld" and then aggregate by Account.
- C. Set up Connect Data Sources in the UI between the "OpportunityWithAccount" and "CaseWithAccount" datasets.
- D. Use a SAQL query to group and join the "OpportunityWithAccount" and "CaseWithAccount" datasets then generate the results.
Answer: D
NEW QUESTION # 74
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