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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Administration | 16% | - Embedding analytics in Salesforce - SAQL query language for dashboard JSON and lens queries - Managing CRM Analytics environment and configurations - Understanding recipes (Data Prep) for visual ETL interface |
| Topic 2: Einstein Discovery | 12% | - Monitoring and interpreting Model Cards to improve or maintain model performance - Adjusting data parameters and adding/removing data or columns to improve models - Analyzing model results and proposing data improvements - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) |
| Topic 3: Analytics Dashboard Implementation | 19% | - Monitoring and optimizing query performance using Dashboard Inspector - Developing selection/result interactions with different query types - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Using advanced functionality such as windowing and time series analysis in compare tables - Configuring dashboards using accurate query types and widget-level parameters - Making dashboards actionable and accessible in Lightning pages |
| Topic 4: Data Layer | 24% | - Incremental sync configuration - Data transformation and loading into Einstein datasets - Understanding denormalized sequential datasets - Troubleshooting failed dataflow jobs - Data extraction from sources - Dataflow configuration for multi-object scenarios |
| Topic 5: Security | 16% | - Implementing security settings for users, groups, and profiles - App sharing based on user and group requirements - Dataset security settings using sharing inheritance and security predicates |
| Topic 6: Analytics Dashboard Design | 13% | - 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 |
Question 1
Which chart type is best suited to track progress of sales revenue that is realized versus the target?
A. Flat gauge
B. Bar chart
C. Pivot table
D. Pie chart
Question 2
A consultant is asked to configure a user to view a dashboard, within a designated app, without the ability to create and save lenses. After adding the user to the app, which action should the consultant take to implement this requirement?
A. Ensure the user has the Use Analytics permission.
B. Assign the Editor role to the user.
C. Assign the Viewer role to the user.
D. Assign the Manager role to the user.
Question 3
A client has a dataset comprised of Opportunity data and Opportunity Line level dat a. The client wants to use this dataset with Einstein Discovery to understand the Opportunity win rate.
What must be done to the dataset to achieve this goal?
A. Click Create Story and Einstein will take care of the rest.
B. Select the isWon = True outcome variable and generate the story.
C. Filter to only look at isWon = True records to avoid skewing the results.
D. Change the grain by removing the line level detail as it will skew the win rate.
Question 4
Einstein Discovery gives you several different kinds of recommended insights. Which of these insights is descriptive?
A. What Happened
B. Why It Happened
C. Predictions & Improvements
D. What Is the Difference
Question 5
A consultant built a very useful Einstein Analytics app for the corporate Sales Operations team of a company that has multiple Salesforce Ogrs, Each Org has similar models and would like to review their data the way that the corporate Sales Operations team does. The app has been packaged and needs to be installed on the other production orgs.
What is the recommended practice to install the custom template app?
A. Metadata API
B. Salesforce Managed Package
C. Change Sets
D. Rest API
Solutions:
| Question 1 Answer: A | Question 2 Answer: A | Question 3 Answer: A | Question 4 Answer: A | Question 5 Answer: B |
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