Salesforce Tableau-CRM-Einstein-Discovery-Consultant : Salesforce Tableau CRM Einstein Discovery Consultant

Tableau-CRM-Einstein-Discovery-Consultant pass collection

Exam Code: Tableau-CRM-Einstein-Discovery-Consultant

Exam Name: Salesforce Tableau CRM Einstein Discovery Consultant

Updated: Jul 18, 2026

Q & A: 244 Questions and Answers

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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Security16%- Dataset security settings using sharing inheritance and security predicates
- Implementing security settings for users, groups, and profiles
- App sharing based on user and group requirements
Topic 2: Einstein Discovery12%- Analyzing model results and proposing data improvements
- Monitoring and interpreting Model Cards to improve or maintain model performance
- Building models by assessing data and selecting prediction types (numeric, binary, multi-classification)
- Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics
- Adjusting data parameters and adding/removing data or columns to improve models
Topic 3: Analytics Dashboard Implementation19%- Implementing delivery management strategies using versioning and/or Dashboard Publisher
- Using advanced functionality such as windowing and time series analysis in compare tables
- Making dashboards actionable and accessible in Lightning pages
- Configuring dashboards using accurate query types and widget-level parameters
- Developing selection/result interactions with different query types
- Monitoring and optimizing query performance using Dashboard Inspector
Topic 4: Administration16%- Managing CRM Analytics environment and configurations
- Understanding recipes (Data Prep) for visual ETL interface
- SAQL query language for dashboard JSON and lens queries
- Embedding analytics in Salesforce
Topic 5: Data Layer24%- Dataflow configuration for multi-object scenarios
- Understanding denormalized sequential datasets
- Incremental sync configuration
- Data extraction from sources
- Data transformation and loading into Einstein datasets
- Troubleshooting failed dataflow jobs
Topic 6: Analytics Dashboard Design13%- Scoping, validating, and prioritizing dashboard design requirements
- Creating dashboards following CRM Analytics best practices and UX design principles
- Identifying appropriate use and configuration of standard CRM Analytics templated apps

Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:

1. A customer has a dataset consisting of over 300 unique product names. They request a prediction model with the product names included.
Which action should the Einstein Consultant take?

A) Run the model using the default variables in the Product object
B) Use SKU numbers rather than product names to increase clarity.
C) Adjust the model to eliminate extreme values in the outcome variable.
D) Split the analysis into multiple models will each having fewer products


2. An Einstein Analytics team reports that when they start their dataflow it runs successfully with no errors or warnings, but one of the fields does not return values when it is queried.
What can be the origin of this issue?

A) The "Integration User Profile" does not have access to the field.
B) The ""Security User Profile" does not have access to the field.
C) The field does not contain any data in Salesforce.
D) The user who runs the dataflow does not have access to the field.


3. A consultant has been brought in to help increase the adaption of Tableau CRM. It has been identified that account managers are struggling to get an overview of their accounts before meeting with them. Ideally they would like to have key details highlighted about active cases and opportunities, opportunity value and product whitespace.
What can the consultant do to increase adoption?

A) Create 4 analytics lenses and embed them onto the account record page
B) Create datasets for account managers to explore
C) Create a dashboard and embed it onto the account record page with a filter based on the viewed account
D) Create a dashboard and embed onto the account record page


4. What's the magic of faceting?

A) It binds charts together so that selecting something in one chart filters other charts by that choice.
B) It creates a chart that shows all the faces of your data in a diamond chart.
C) It shifts the time period of the chart you're viewing.
D) It turns the dataflow on and off.


5. In a Compare Table formula, you can refer to other columns with:

A) All of the above
B) Letters (A..Z)
C) Their names
D) Numbers (1..9)


Solutions:

Question # 1
Answer: B
Question # 2
Answer: C
Question # 3
Answer: C
Question # 4
Answer: A
Question # 5
Answer: B

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