Updated for Winter '26 Release
Last Updated: November 2025 | Exam Version: Winter '26
This exam guide reflects the latest Salesforce Winter '26 release (November 2025). Key updates include AI-Powered Data Prep (Agentforce), Direct Discovery on Data Cloud objects, and new AI-Generated Narratives.
⚡ What Changed from Spring '25 to Winter '26?
Agentforce AI now suggests joins, transformations, and anomaly detection in Data Recipes
Run Einstein Discovery models directly on Data Cloud Data Model Objects (DMOs)
New dashboard widget uses generative AI to write natural language summaries of KPIs
Salesforce Certified CRM Analytics and Einstein Discovery Consultant
Your complete guide to building insights, predictions, and analytics apps
📊 Exam At a Glance
📝 Note: As of July 21, 2025, all Salesforce exams are delivered through Pearson VUE (Trailhead Academy). The exam can be taken at a testing center or online with remote proctoring.
Exam Objectives & Weightage
1. Data Layer: Preparation & Management
32%Design and build the data layer, including data ingestion, transformation, and cleansing. Master Data Recipes, Dataflows, and connectors to prepare data for analysis.
This section now includes AI-Powered Data Prep, where Agentforce suggests joins, transformations, and anomaly detection in Data Recipes.
View Key Topics ▼
- Describe the use cases for Data Sync, Dataflows, and Recipes
- Connect to Salesforce and external data sources
- Design and build Data Recipes with joins, appends, and transformations
- Manage data for performance (e.g., data filtering)
2. Visualization: Dashboards & Apps
28%Build advanced dashboards and apps. This includes faceting, query binding (SAQL), and designing purpose-built layouts for different audiences and devices.
The new AI-Generated Narratives widget is a testable feature for adding AI-driven text summaries to dashboards and apps.
3. Einstein Discovery: Stories & Predictions
25%Configure and run Einstein Discovery Stories to analyze outcomes, find key drivers, and get recommendations. Deploy prediction models and embed insights in Salesforce.
Expect scenarios on Direct Discovery on DMOs, allowing models to run directly on Data Cloud objects without intermediate datasets.
📝 Sample Exam Questions
💡 Test Your Knowledge
These sample questions reflect the style and difficulty level of the actual Consultant exam. Practice with these to assess your readiness.
Question 1: Data Layer
A consultant needs to combine Opportunity data from Salesforce with an external Quota CSV file to create a single dataset for a sales dashboard. What is the recommended tool for this transformation?
A) Dataflow
B) Data Recipe
C) A SAQL Query
D) Data Sync Connector
✓ Correct Answer: B) Data Recipe
Explanation: Data Recipes are the modern, recommended tool for data transformation and preparation. They provide a visual interface for joining (e.g., Salesforce + CSV data), appending, and transforming data. Dataflows are the legacy tool.
Question 2: Visualization
A manager wants a dashboard where they can click on a 'Region' in a map chart, and a separate 'Account' list widget on the same dashboard automatically filters to show only Accounts in that selected region. How should this interactivity be enabled?
A) Query Binding
B) Faceting
C) A SAQL Query
D) Einstein Discovery
✓ Correct Answer: B) Faceting
Explanation: Faceting is the standard, out-of-the-box feature that allows widgets (steps) from the same dataset to filter each other automatically. Query Binding is used for more complex, custom interactions, but faceting solves this simple use case.
Question 3: Einstein Discovery
A sales director wants to know the *key factors* that lead to a 'Won' Opportunity and get suggestions on how to improve the win rate for in-flight deals. What tool is BEST suited for this requirement?
A) A CRM Analytics Dashboard with a "Win Rate" number widget
B) An Einstein Discovery Story to maximize "IsWon"
C) A Data Recipe with a transformation formula
D) A Salesforce Standard Report
✓ Correct Answer: B) An Einstein Discovery Story to maximize "IsWon"
Explanation: Einstein Discovery is designed to analyze historical outcomes (Won/Lost) to find key drivers (factors) and provide prescriptive recommendations. Dashboards show *what* happened, while Discovery explains *why* it happened and *what to do*.
Question 4: Visualization (Winter '26 Feature)
A consultant is building a dashboard and wants to add a text summary that *automatically* describes the key insights from the charts in plain English. What new Winter '26 feature should they use?
A) A Text Widget with a bound SAQL query
B) AI-Powered Data Prep
C) The AI-Generated Narratives widget
D) Direct Discovery on DMOs
✓ Correct Answer: C) The AI-Generated Narratives widget
Explanation: The new AI-Generated Narratives widget (Winter '26) uses generative AI to automatically create a natural language summary of the dashboard's KPIs, fulfilling the requirement for an "automatic" text summary.
💡 Exam Tip: This exam is *not* just about building. It's about data security. Know row-level security, sharing inheritance, and security predicates inside and out. They are critical and heavily tested.
📚 Study Resources & Preparation
🎯 Recommended Study Plan (4-6 Weeks)
Confirm Admin cert. Master Data Layer: Connectors, Recipes, and Dataflows. Build several complex datasets.
Build dashboards. Practice faceting, query binding (SAQL), and data security (predicates, inheritance).
Master Einstein Discovery. Build stories, interpret insights, and deploy models. Take practice exams.
💡 Exam Day Tips
Recipes are the modern data prep tool. Unless a question specifically mentions legacy Dataflows, always choose Recipe for transformations.
CRM Analytics Dashboards show *what* happened. Einstein Discovery explains *why* it happened and *what to do* about it.
Understand the difference: Sharing Inheritance (follows Salesforce sharing) vs. Security Predicates (custom row-level filter logic).