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The Salesforce Tableau CRM Einstein Discovery Consultant certification exam consists of 60 multiple-choice questions and must be completed within 105 minutes. Tableau-CRM-Einstein-Discovery-Consultant exam is administered online and can be taken from anywhere with an internet connection. Tableau-CRM-Einstein-Discovery-Consultant exam covers a wide range of topics, including understanding the capabilities and limitations of Tableau CRM and Einstein Discovery, designing and deploying analytics solutions, and configuring and optimizing Salesforce integrations.
Salesforce Tableau CRM Einstein Discovery Consultant exam is designed to test an individual's expertise in implementing and configuring the Tableau CRM Einstein Discovery platform. Salesforce Tableau CRM Einstein Discovery Consultant certification is ideal for professionals who work with data analytics, machine learning, and business intelligence. Tableau-CRM-Einstein-Discovery-Consultant exam is intended for consultants who are responsible for designing and implementing solutions that help organizations gain insights into their data.
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Salesforce Tableau-CRM-Einstein-Discovery-Consultant Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| 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 |
| Analytics Dashboard Design | 13% | - Scoping, validating, and prioritizing dashboard design requirements - Identifying appropriate use and configuration of standard CRM Analytics templated apps - Creating dashboards following CRM Analytics best practices and UX design principles |
| Einstein Discovery | 12% | - Analyzing model results and proposing data improvements - Building models by assessing data and selecting prediction types (numeric, binary, multi-classification) - Monitoring and interpreting Model Cards to improve or maintain model performance - Adjusting data parameters and adding/removing data or columns to improve models - Enabling prediction features on Lightning record pages across Salesforce and CRM Analytics |
| Data Layer | 24% | - Data transformation and loading into Einstein datasets - Incremental sync configuration - Data extraction from sources - Dataflow configuration for multi-object scenarios - Troubleshooting failed dataflow jobs - Understanding denormalized sequential datasets |
| Analytics Dashboard Implementation | 19% | - Developing selection/result interactions with different query types - Monitoring and optimizing query performance using Dashboard Inspector - 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 - Implementing delivery management strategies using versioning and/or Dashboard Publisher |
| 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 |
