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| Section | Weight | Objectives |
|---|---|---|
| Einstein Discovery | 12% | - 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 - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) - Analyzing model results and proposing data improvements |
| Analytics Dashboard Implementation | 19% | - Developing selection/result interactions with different query types - Implementing delivery management strategies using versioning and/or Dashboard Publisher - Making dashboards actionable and accessible in Lightning pages - 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 |
| Data Layer | 24% | - Understanding denormalized sequential datasets - Data extraction from sources - Data transformation and loading into Einstein datasets - Dataflow configuration for multi-object scenarios - Troubleshooting failed dataflow jobs - Incremental sync configuration |
| 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 |
| Security | 16% | - App sharing based on user and group requirements - Implementing security settings for users, groups, and profiles - Dataset security settings using sharing inheritance and security predicates |
| 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 |
1. A Senior Sales Business Analyst asks for a dashboard that contains fiscal year product opportunities. Information is maintained in a spreadsheet which is comprehensive, but its contents often need to be explained. After sketching the dashboard, the consultant is ready to start building.
Which concept should be applied to this dashboard?
A) Use charts to help users ask questions, not illustrate a conclusion.
B) Design the dashboard with the desktop in mind and use the same layout for mobile devices for consistency.
C) Use the different chart types to make the dashboard interesting and appealing.
D) Limit widget actions and exploration so users will focus only on the high-level information.
2. A story created has an AUC of .62.
What two things could be done to possible improve this AUC score?
Choose 2 answers
A) Change the order of the story insights to descending.
B) Run detect sentiment on the dataflow before creating the story.
C) Add more rows of relevant data.
D) Segment the training set.
3. What are two main steps for creating a dataset?
A) Build and explore
B) Run and monitor
C) Plan and map
D) Extract and prepare
4. How do you create a regression timeseries?
5. What is a keyword in SAQL? And what case must it be in?
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A,B | Question # 3 Answer: D | Question # 4 Answer: Only visible for members | Question # 5 Answer: Only visible for members |
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