To be eligible for the certification exam, candidates are required to have a minimum of six months of experience working with the Salesforce Einstein Analytics and Discovery platform. They must also have completed the recommended training courses and have a good understanding of the platform's capabilities and limitations. Candidates are also expected to have a solid understanding of data analytics and business intelligence concepts, as well as familiarity with data modeling and data preparation tools.
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Salesforce Einstein-Analytics-and-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Administration and Configuration | 17% | - Performance optimization and limits - Template apps and API usage - Platform setup and deployment - Migration and change management |
| Topic 2: Einstein Discovery | 12% | - Story creation and interpretation - Model deployment and write-back - Predictions in dashboards and Salesforce objects - Data preparation for modeling |
| Topic 3: Analytics Dashboard Design | 13% | - Chart selection and UX best practices - Layout and mobile optimization - Lens creation and SAQL basics |
| Topic 4: Security and Access | 16% | - Row-level security and sharing inheritance - Predicate expressions and encryption - App and dataset permissions - User provisioning and governance |
| Topic 5: Data Layer | 23% | - Data sync, dataflows and recipes - Schema, XMD and derived fields - Dataset creation, transformation and management - Data ingestion and connectors |
| Topic 6: Analytics Dashboard Implementation | 19% | - Bindings, interactivity and filters - Dashboard embedding and performance - Advanced SAQL and custom logic |
