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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security | 16% | - App sharing based on user and group requirements - Dataset security settings using sharing inheritance and security predicates - Implementing security settings for users, groups, and profiles |
| Topic 2: Analytics Dashboard Design | 13% | - Identifying appropriate use and configuration of standard CRM Analytics templated apps - Scoping, validating, and prioritizing dashboard design requirements - Creating dashboards following CRM Analytics best practices and UX design principles |
| Topic 3: Einstein Discovery | 12% | - Monitoring and interpreting Model Cards to improve or maintain model performance - 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 - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics |
| Topic 4: Administration | 16% | - Embedding analytics in Salesforce - Managing CRM Analytics environment and configurations - SAQL query language for dashboard JSON and lens queries - Understanding recipes (Data Prep) for visual ETL interface |
| Topic 5: Analytics Dashboard Implementation | 19% | - Monitoring and optimizing query performance using Dashboard Inspector - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Configuring dashboards using accurate query types and widget-level parameters - Developing selection/result interactions with different query types - Making dashboards actionable and accessible in Lightning pages - Using advanced functionality such as windowing and time series analysis in compare tables |
| Topic 6: Data Layer | 24% | - Data extraction from sources - Understanding denormalized sequential datasets - Troubleshooting failed dataflow jobs - Data transformation and loading into Einstein datasets - Dataflow configuration for multi-object scenarios - Incremental sync configuration |
Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:
A consultant has created a story to maximize the daily sales quantity of consumer products in stores. After creating a story, the consulting is presented with this data alert by Einstein Discovery (see graphic).
What are two appropriate actions to take?
Choose 2 answers
- A. Discuss with the client if values below 0 and above 2,489 are so uncommon that they should perhaps be left out of the story.
- B. Remove the outliers as suggested by Einstein, and verify using model metrics and story insights if the quality improved.
- C. Remove the outliers as suggested by Einstein and deploy the model.
- D. Manually remove the sales bellow 0 (negative sales must be a data issue), but keep the large value (the more data, the better the model will be).
A dashboard dataset is growing and the Einstein Analytics consultant notices an impact on performance. The consultant needs to make a few adjustments.
Which three actions can the consultant take to improve dashboard performance? Choose 3 answers
- A. Move calculations to a dataflow.
- B. Use SAQL code to join datasets at runtime.
- C. Distribute steps among separate pages.
- D. Replace separate step filters with a global filter.
- E. Reorganize the dashboard widgets.
The Einstein Analytics Plus Platform license is enabled for a Salesforce org and assigned to each user. However, these users cannot see the Einstein Analytics Studio in the App Launcher.
How can this issue be addressed?
- A. Assign the users to the permission set containing Use Analytics.
- B. Assign the users to the permission set containing Manage Analytics.
- C. Create user accounts for the users in Einstein Analytics.
- D. Share the app with the users in Einstein Analytics.
A story created has an AUC of .62.
What two things could be done to possible improve this AUC score?
Choose 2 answers
- A. Segment the training set.
- B. Change the order of the story insights to descending.
- C. Add more rows of relevant data.
- D. Run detect sentiment on the dataflow before creating the story.
A consultant is asked to create a dashboard for sales to see the forecasted sales per product family. After gathering the requirements, the consultant decides to leverage the timeseries SAQL statement to predict sales.
Which two actions must be performed when writing the SAQL query?
Choose 2 answers
- A. Validate that there is enough data in the dataset to make a good prediction.
- B. Investigate which prediction model is best for the data available.
- C. Include the fill SAQL statement to fill any missing dates.
- D. Determine if the timeseries required parameter, prediction interval, should be 80 or 95.
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