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Updated: Oct 15, 2026
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Salesforce Einstein-Analytics-and-Discovery-Consultant日本語 Exam Overview:
| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Einstein Analytics and Discovery Consultant |
| Exam Number: | Einstein-Analytics-and-Discovery-Consultant / Analytics-Con-201 |
| Exam Format: | Scenario-based, Multiple-choice, Multiple-select |
| Passing Score: | 68% |
| Certificate Validity Period: | 3 years (requires annual maintenance) |
| Exam Duration: | 90 minutes |
| Related Certifications: | Salesforce Certified Tableau CRM and Einstein Discovery Consultant Salesforce Certified Administrator |
| Exam Price: | USD 200 (plus applicable taxes; retake fee USD 100) |
| Available Languages: | English |
| Real Exam Qty: | 60 (plus up to 5 unscored items) |
| Recommended Training: | Trailhead Study Trails Official Exam Guide |
| Exam Registration: | Salesforce Certification Portal |
| Sample Questions: | Salesforce Einstein-Analytics-and-Discovery-Consultant日本語 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE / PSI testing centers |
| Pre Condition: | No mandatory prerequisites; recommended 1+ year hands-on experience with Einstein Analytics, Salesforce Admin knowledge helpful |
| Official Syllabus URL: | https://developer.salesforce.com/resources2/certification-site/files/SGCertifiedEinsteinAnalyticsandDiscoveryConsultant.pdf |
Salesforce Einstein Analytics and Discovery Consultant certification exam is a challenging test that requires a deep understanding of the Salesforce Einstein Analytics and Discovery platform. Einstein-Analytics-and-Discovery-Consultant-JPN exam consists of 60 multiple-choice questions and lasts for 105 minutes. To pass the exam, you must achieve a score of 65% or higher. Einstein-Analytics-and-Discovery-Consultant-JPN exam covers a range of topics, including data modeling, data preparation, data visualization, and advanced analytics concepts.
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.
The Salesforce Einstein Analytics and Discovery Consultant (Einstein-Analytics-and-Discovery-Consultant日本語版) certification exam is a multiple-choice exam consisting of 60 questions that must be completed within 105 minutes. Einstein-Analytics-and-Discovery-Consultant-JPN exam is delivered online and is available in multiple languages. Candidates who pass the exam are awarded the Salesforce Einstein Analytics and Discovery Consultant Certification, which is a globally recognized certification that demonstrates their expertise in designing and implementing analytics solutions using the Salesforce Einstein Analytics platform.
Salesforce Einstein-Analytics-and-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Einstein Discovery | 12% | - Story creation and interpretation - Data preparation for modeling - Predictions in dashboards and Salesforce objects - Model deployment and write-back |
| Analytics Dashboard Design | 13% | - Lens creation and SAQL basics - Layout and mobile optimization - Chart selection and UX best practices |
| Administration and Configuration | 17% | - Template apps and API usage - Performance optimization and limits - Platform setup and deployment - Migration and change management |
| Security and Access | 16% | - App and dataset permissions - Predicate expressions and encryption - User provisioning and governance - Row-level security and sharing inheritance |
| Analytics Dashboard Implementation | 19% | - Dashboard embedding and performance - Advanced SAQL and custom logic - Bindings, interactivity and filters |
| Data Layer | 23% | - Data ingestion and connectors - Schema, XMD and derived fields - Dataset creation, transformation and management - Data sync, dataflows and recipes |
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