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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Analytics Dashboard Design | 13% | - Scoping, validating, and prioritizing dashboard design requirements - Identifying appropriate use and configuration of standard CRM Analytics templated apps - Creating dashboards following CRM Analytics best practices and UX design principles |
| Einstein Discovery | 12% | - Analyzing model results and proposing data improvements - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) - Adjusting data parameters and adding/removing data or columns to improve models - Monitoring and interpreting Model Cards to improve or maintain model performance - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics |
| Analytics Dashboard Implementation | 19% | - Monitoring and optimizing query performance using Dashboard Inspector - Making dashboards actionable and accessible in Lightning pages - Using advanced functionality such as windowing and time series analysis in compare tables - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Developing selection/result interactions with different query types - Configuring dashboards using accurate query types and widget-level parameters |
| Administration | 16% | - Embedding analytics in Salesforce - Understanding recipes (Data Prep) for visual ETL interface - SAQL query language for dashboard JSON and lens queries - Managing CRM Analytics environment and configurations |
| Security | 16% | - App sharing based on user and group requirements - Implementing security settings for users, groups, and profiles - Dataset security settings using sharing inheritance and security predicates |
| Data Layer | 24% | - Troubleshooting failed dataflow jobs - Incremental sync configuration - Understanding denormalized sequential datasets - Data extraction from sources - Data transformation and loading into Einstein datasets - Dataflow configuration for multi-object scenarios |
Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:
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, 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
- 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, Q use "append" transformation to add case data with account data, store as a dataset, and then build a dashboard using the generated dataset
Correct Answer: B,C 🗳️
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. Use a SAQL query to group and join the "OpportunityWithAccount" and "CaseWithAccount" datasets then generate the results.
- 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. 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.
Correct Answer: A 🗳️
What does a configuration wizard do?
- A. Customizes your template based on Salesforce settings
- B. Lets you know the best way to set up your Salesforce data
- C. Asks you questions about how you store data in your org to help you create your app
- D. Automatically creates multiple versions of the same app
Correct Answer: C 🗳️
Explanation: Only visible for RealVCE members. You can sign-up / login (it's free).
Why are insights in the Unrelated category important?
- A. They explain everything about the outcome.
- B. They explain how interaction terms affect the outcome.
- C. They aren't important. Hence the name, Unrelated.
- D. The outcome might not have much to do with related variables. It might have more to do with global effects.
Correct Answer: D 🗳️
Universal Containers is evaluating the connection mode for the objects in their local Salesforce connector. They want to only sync updated and new records from the Order object, but they have some formula fields on the object and want to ensure those are updated weekly.
which
Which connection mode is best suited for this purpose?
- A. Full Sync
- B. periodic Incremental Sync
- C. Periodic Full Sync
- D. Incremental Sync
Correct Answer: B 🗳️
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