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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Analytics Dashboard Implementation | 19% | - Configuring dashboards using accurate query types and widget-level parameters - 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 - Monitoring and optimizing query performance using Dashboard Inspector |
| Administration | 16% | - SAQL query language for dashboard JSON and lens queries - Embedding analytics in Salesforce - Managing CRM Analytics environment and configurations - Understanding recipes (Data Prep) for visual ETL interface |
| Security | 16% | - Implementing security settings for users, groups, and profiles - Dataset security settings using sharing inheritance and security predicates - App sharing based on user and group requirements |
| Einstein Discovery | 12% | - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) - Analyzing model results and proposing data improvements - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics - Monitoring and interpreting Model Cards to improve or maintain model performance - Adjusting data parameters and adding/removing data or columns to improve models |
| Data Layer | 24% | - Data extraction from sources - Data transformation and loading into Einstein datasets - Troubleshooting failed dataflow jobs - Incremental sync configuration - Understanding denormalized sequential datasets - Dataflow configuration for multi-object scenarios |
| Analytics Dashboard Design | 13% | - Creating dashboards following CRM Analytics best practices and UX design principles - Identifying appropriate use and configuration of standard CRM Analytics templated apps - Scoping, validating, and prioritizing dashboard design requirements |
Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:
1. Default # rows in compare table.
A) 3000
B) 2000
C) 1500
D) 1000
2. A company's Salesforce org has multi-currency enabled. This company's business intelligence team used Einstein Analytics to build a dataflow that creates a dataset, "OpportunityDataSet". This dataset is populated with data extracted from the standard object, Opportunity. One of the extracted fields is the standard field, Amount.
If a user explores the "OpportunityDataSet" in Einstein Analytics, in which currency will the Amount values be shown?
A) In the currency that is set on the "currency" attribute in the dataflow
B) In the integration user's currency
C) In the connected user's currency
D) In the currency that is set on the "currency" attribute in the dataset
3. What are Einstein Analytics prebuilt permission sets? Select 2:
A) Einstein Analytics Platform Admin
B) Einstein Analytics Superadmin
C) Einstein Analytics Platform User
D) Einstein Analytics
4. Can you share data from a widget?
A) Select the step of the widget and share data.
B) Select "Share" icon, click on "Download", and select "Download in .png, .XLS, or CSV" format.
C) Only with the proper Einstein Analytics Platform license.
D) No, you can't share data from a widget.
5. Refer to the graphic.
Which conclusion can be made regarding the strength of the model shown?
A) The strength of the model cannot be determined with the metrics shown.
B) The model is very weak and doesn't provide useful predictions due to the low threshold.
C) The model is very strong. A GINI coefficient of .535 shows that this model is very effective.
D) The model is pretty good; the accuracy rating of .7597 means we can predict both wins and losses at a fairly high rate.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: A,C | Question # 4 Answer: B | Question # 5 Answer: B |
