Salesforce CRM Analytics and Einstein Discovery Consultant

About the Salesforce CRM Analytics and Einstein Discovery Consultant Certification

The Salesforce CRM Analytics and Einstein Discovery Consultant certification is designed for professionals who implement data-driven, AI-powered solutions at the enterprise level using Salesforce’s analytics platform. This credential validates your ability to design, build, and support robust apps, datasets, dashboards, and predictive models within the Lightning Experience.

This certification assesses your knowledge across the full CRM Analytics and Einstein Discovery toolset — from data ingestion and modeling to visualization and predictive insights — with a strong focus on practical implementation and real-world business use cases.

Who Should Take This Certification

This exam is ideal for consultants, data analysts, and Salesforce professionals who:

• Have at least 1 year of hands-on experience with CRM Analytics and Einstein Discovery.

• Possess a broad understanding of dataset management, permissions and security, SAQL, and JSON for dashboard configuration.

• Are involved in delivering enterprise analytics solutions within the Salesforce ecosystem.

Key Skills Measured

Front-End Capabilities

• Choose appropriate visualizations to meet business needs

• Build dashboards using UX best practices and CRM Analytics tools

• Write advanced SAQL, SOQL, or SQL queries

• Configure interactions and bindings (selection/result)

• Connect and display multiple data sources within dashboards

• Customize Salesforce-provided templates and enhance user interfaces

• Use compare tables, pivot tables, and dynamic calculations

• Optimize dashboard performance with Dashboard Inspector

• Create responsive layouts for mobile and desktop

• Embed pages and components across Salesforce experiences

Administrative Functions

• Manage user access and provisioning

• Deploy analytics assets across environments

• Apply governance strategies to maintain data integrity and consistency

• Implement row-level security with security predicates and sharing inheritance

• Set app-level permissions and control visibility

• Embed dashboards in Salesforce pages, including Experience Cloud

• Understand CRM Analytics API usage at a high level

Back-End & Data Management

• Ingest data using data sync, recipes, and dataflows

• Build and schedule efficient dataflows and recipes

• Work around sync limitations and performance constraints

• Add derived fields in dataflows, recipes, or the UI

• Export and prepare data for Einstein Discovery

• Create and evaluate predictive models using Einstein Discovery

• Monitor and interpret model accuracy with Model Manager

• Deliver prescriptive insights and deploy models to Salesforce records

• Surface AI recommendations in the user interface to support decision-making

What You’re Not Expected to Know

This certification does not require knowledge of the following:

• Apex programming

• Salesforce SDKs or custom APIs

• Advanced data serialization methods

• Salesforce Data Pipelines or Data Cloud

• Data backup strategies

• GeoJSON map creation

• Hierarchical/Territorial security models

• Data scaffolding or imputation techniques

Exam Outline

The Salesforce Certified CRM Analytics and Einstein Discovery Consultant Exam measures a candidate’s knowledge and skills related to the following objectives.

Admin/Configuration: 17%

• Given business and access requirements, enable CRM Analytics along with its features, encompassing permission sets and licenses.

• Given a scenario, use CRM Analytics to design a solution that accommodates data sync/dataflows/recipes limits.

• Given a situation, demonstrate knowledge of what can be accomplished with the CRM Analytics API.

• Given business requirements, migrate between different environments for deployment.

Data Layer: 23%

• Given data sources, use Data Manager to extract and load the data into the CRM Analytics application to create datasets.

• Given business needs and consolidated data, implement refreshes for data syncs and dataflows/recipes while keeping limits and considerations in mind.

• Given business/user requirements, perform data transformations in dataflows/recipes.

• Given user requirements or ease of use strategies, manage dataset extended metadata (XMD) by editing labels, values, and colors.

• Implement delivery management strategies in dataflows/recipes including versioning and conversion.

Security: 16%

• Given governance and CRM Analytics asset security requirements, implement necessary security settings for users, groups, and profiles.

• Given row-based security requirements, implement the appropriate dataset security settings by using sharing inheritance and security predicates.

• Implement app sharing based on user and group requirements.

Analytics Dashboard Design: 13%

• Given business requirements, scope, validate, and prioritize dashboard design requirements.

• Create appropriate dashboards to meet business requirements following CRM Analytics best practices and UX design principles.

• Identify the appropriate use and configuration of a standard CRM Analytics templated app to meet business requirements.

Analytics Dashboard Implementation: 19%

• Given business requirements, configure dashboards using accurate query types and widget level parameters.

• Given business requirements, develop selection/result interactions with different types of queries.

• Given business requirements, use advanced functionality such as windowing and time series analysis within compare tables.

• Given business requirements, make dashboards actionable and accessible in Lightning pages.

• Given a scenario, monitor and optimize query performance using Dashboard Inspector.

• Implement delivery management strategies using versioning and/or Dashboard Publisher.

Einstein Discovery: 12%

• Build a model by assessing data and selecting one of the three types of predictions (numeric, binary, multi-classification).

• Given business requirements, analyze the model results and propose data improvements to the customer.

• Given derived results and insights from the model, adjust data parameters and add/remove data or columns to improve the model.

• Enable prediction features on Lightning record pages across Salesforce and CRM Analytics.

• Monitor and interpret a Model Card to improve or maintain model performance.