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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 |
| Topic 2: Analytics Dashboard Implementation | 19% | - Making dashboards actionable and accessible in Lightning pages - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Developing selection/result interactions with different query types - Using advanced functionality such as windowing and time series analysis in compare tables - Monitoring and optimizing query performance using Dashboard Inspector - Configuring dashboards using accurate query types and widget-level parameters |
| Topic 3: 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 - Adjusting data parameters and adding/removing data or columns to improve models - Monitoring and interpreting Model Cards to improve or maintain model performance |
| Topic 4: Administration | 16% | - Understanding recipes (Data Prep) for visual ETL interface - Embedding analytics in Salesforce - Managing CRM Analytics environment and configurations - SAQL query language for dashboard JSON and lens queries |
| Topic 5: Analytics Dashboard Design | 13% | - Identifying appropriate use and configuration of standard CRM Analytics templated apps - Creating dashboards following CRM Analytics best practices and UX design principles - Scoping, validating, and prioritizing dashboard design requirements |
| Topic 6: Data Layer | 24% | - Data extraction from sources - Incremental sync configuration - Dataflow configuration for multi-object scenarios - Understanding denormalized sequential datasets - Data transformation and loading into Einstein datasets - Troubleshooting failed dataflow jobs |
Salesforce Tableau CRM Einstein Discovery Consultant Sample Questions:
1. Upper and lower limits on columns (vars) in discovery:
A) 20 column minimum, 50 maximum
B) 2 column minimum, 50 maximum
C) 10 column minimum, 200 maximum
D) 2 column minimum, 25 maximum
2. The Tableau CRM team at a company has created three dataflows.
myDataflowOne: this dataflow tasks 2 hours to run.
myDataflowOne: this dataflow tasks 1 hours and 30 minutes to run
myDataflowOne: this dataflow tasks 1 minute and 30 seconds to run.
If all three dataflows run, how many count towards the limit?
A) 3
B) 2
C) 1
D) 0
3. What are the two main parts of a lens/exploration?
A) Measure
B) Query
C) Dataset
D) Visualization
E) Grouping
4. A consultant built an Einstein Analytics app for the Sales Operations team. The Sales Operations team wants to share their app with other people at the company. The consultant recommends distributing the app as an Einstein Analytics template app.
What can the consultant do to give the Sales team more choices and options with future apps that are generated from the Sales Operations app'
A) Update contents in the Sales Operations app and create new template versions of the app.
B) Ensure the Sales team has the necessary permissions to customize their apps.
C) Create a configuration wizard for the app.
D) Update contents in the Sales Operations app and changes will be pushed down to its generated apps.
5. As part of their analysis, Yasmine, Tonya, and Hadiqa need to create and save lenses to their project app. What is the minimum app role they need to do this?
A) Manager
B) Designer
C) Editor
D) Viewer
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A | Question # 3 Answer: D,E | Question # 4 Answer: C | Question # 5 Answer: C |
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