Salesforce Einstein Analytics and Discovery Consultant Exam is a challenging exam that requires a solid understanding of the entire Salesforce platform. Candidates must also have experience in data analytics and visualization, as well as familiarity with Salesforce Einstein Analytics and Discovery. Einstein-Analytics-and-Discovery-Consultant-JPN exam consists of 60 multiple-choice questions and lasts for 105 minutes. Candidates are required to score 65% or higher to pass the exam and earn the certification.
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To pass the Salesforce Einstein Analytics and Discovery Consultant exam, candidates must demonstrate their knowledge of various topics related to Salesforce Einstein Analytics and Discovery, such as data modeling, data preparation, dashboard and report design, and data analysis. Einstein-Analytics-and-Discovery-Consultant-JPN exam consists of 60 multiple-choice questions and must be completed within 105 minutes. Candidates must achieve a passing score of 65% or higher to earn the certification.
Reference: https://trailhead.salesforce.com/help?article=Salesforce-Certified-Einstein-Analytics-and-Discovery-Consultant-Exam-Guide
Salesforce Einstein Analytics and Discovery Consultant Certification Exam is a valuable certification for professionals who are responsible for designing and implementing analytics solutions using the Salesforce Einstein Analytics platform. It validates the skills and knowledge of candidates in a range of areas including data modeling, data visualization, dashboard design, and analytics best practices. With the right preparation and training, candidates can successfully pass the exam and earn this globally recognized certification.
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Salesforce Einstein-Analytics-and-Discovery-Consultant日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Security | 16% | - Data Security
- 1. Sharing Inheritance
- 2. Row-Level Security
- 3. Security Predicates
- Access Control
- 1. Profile and Permission Configuration
- 2. User and Group Security
|
| Admin and Configuration | 17% | - CRM Analytics Enablement and Licensing
- 1. Permission Sets and Access Management
- 2. Feature Enablement
- Deployment and Migration
- 1. Environment Migration Strategies
- 2. Analytics API Capabilities
|
| Einstein Discovery | 12% | - Model Analysis and Deployment
- 1. Prediction Deployment
- 2. Model Evaluation
- 3. Model Card Monitoring
- 4. Data Improvement Recommendations
- Prediction Models
- 1. Multi-Class Predictions
- 2. Binary Predictions
- 3. Numeric Predictions
|
| Analytics Dashboard Implementation | 19% | - Dashboard Development
- 1. Interactions and Bindings
- 2. Compare Tables and Time Series Analysis
- 3. Widgets and Query Types
- Performance and Deployment
- 1. Lightning Page Integration
- 2. Versioning and Dashboard Publisher
- 3. Dashboard Inspector
|
| Data Layer | 23% | - Data Transformation
- 1. Refresh and Delivery Management
- 2. Dataflows
- 3. Recipes
- 4. Dataset Metadata Management
- Data Integration
- 1. Data Manager
- 2. Dataset Creation
- 3. Data Sync
|
| Analytics Dashboard Design | 13% | - Dashboard Architecture
- 1. Templated Applications
- 2. UX Best Practices
- Requirements Gathering
- 1. Business Requirement Analysis
- 2. Dashboard Scope and Prioritization
|