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| Section | Weight | Objectives |
|---|---|---|
| Analytics Dashboard Implementation | 19% | - Developing selection/result interactions with different query types - Monitoring and optimizing query performance using Dashboard Inspector - 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 |
| 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 |
| Data Layer | 24% | - Incremental sync configuration - Dataflow configuration for multi-object scenarios - Data extraction from sources - Understanding denormalized sequential datasets - Data transformation and loading into Einstein datasets - Troubleshooting failed dataflow jobs |
| 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 |
| Einstein Discovery | 12% | - 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 - Monitoring and interpreting Model Cards to improve or maintain model performance - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) |
| Administration | 16% | - SAQL query language for dashboard JSON and lens queries - Understanding recipes (Data Prep) for visual ETL interface - Embedding analytics in Salesforce - Managing CRM Analytics environment and configurations |
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