Salesforce Einstein Analytics
- Product Code: eeb101
- Exam Questions: 242
- Vendor: salesforce
$9.99
$12.99- Updated At: Nov 14, 2024
Salesforce Einstein Analytics Developer Certification
Validate your skills and knowledge to develop Einstein Analytics solutions for business users, including data modeling, data preparation, and analytics development.
Focus
The Salesforce Einstein Analytics certification focuses on Einstein Analytics development, data modeling, data preparation, and analytics development
Exam Duration
The Salesforce Einstein Analytics exam duration is 105 minutes
Num of Question
The exam contains a total of 68
Exam Fee
The exam fee is $245.
Exam Validity
The CCRN-Pediatric certification is valid for Retirement: N/A, Renewal: 1 year.
Prior Certification
- Einstein Analytics Administrator Certification
Exam Format
The Salesforce Einstein Analytics exam is a Multiple Choice, Multiple Select, and Performance-Based Questions
Passing Conditions
To pass Salesforce Einstein Analytics exam, applicants must achieve a minimum score of Pass the exam with a minimum score of 56%
Who Should Take
Admins, developers, and architects who want to validate their skills and knowledge to develop Einstein Analytics solutions for business users.
- Einstein Analytics Developer
- Einstein Analytics Administrator
- Business Analyst
Prerequisites
N/A
Or can substitute with certifications:
- Einstein Analytics Administrator Certification
Certification Process
- Register for the exam
- Prepare for the exam by studying the Einstein Analytics Developer Certification Exam Study Guide
- Take the exam and pass with a minimum score of 56%
- Maintain your certification by completing ongoing training and continuing education requirements
Domains with Weights
- Einstein Analytics Development Fundamentals (20%): Describe the benefits of using Einstein Analytics, explain the role of a developer, and understand the requirements for developing and deploying analytics solutions.
- Data Modeling and Data Preparation (30%): Describe data discovery and modeling options, understand data preparation and data cleansing, and explain how to build and manage data models.
- Analytics Development (30%): Describe how to develop visualizations and dashboards, explain how to use Einstein Analytics APIs and data sources, and demonstrate understanding of predictive analytics and machine learning.
- Security and Governance (20%): Describe data security and governance options in Einstein Analytics, explain how to manage user access and data permissions, and understand the requirements for data encryption and data archiving.
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