Salesforce CRM Analytics and Einstein Discovery Consultant Certification Guide

Current study overview for the Salesforce CRM Analytics and Einstein Discovery Consultant credential, verified against Salesforce's credential catalog on July 19, 2026.

Study illustration for Salesforce CRM Analytics and Einstein Discovery Consultant Certification Guide

Study map for Salesforce CRM Analytics and Einstein Discovery…. Confirm objectives on current Salesforce sources.

Salesforce CRM Analytics and Einstein Discovery Consultant

Catalog status checked July 19, 2026: Available.

Current credential snapshot

Item Current listing
Credential Salesforce CRM Analytics and Einstein Discovery Consultant
Track Consultant
Level in source inventory Mid
Exam code in source inventory Analytics-Con-201
Price in source inventory $200 USD
Availability Available

Exam format, objectives, pricing, and prerequisites can change. Confirm those details in Salesforce’s current exam guide before purchasing or scheduling an exam.

Study overview

📊 Stop guessing and start predicting with the power of AI-driven insights.Salesforce Certified CRM Analytics and Einstein Discovery Consultant

Mastering the art of data transformation, predictive modeling, and enterprise-grade visualization.


At a Glance

Feature Details
Exam Code Analytics-Con-201
Duration 90 minutes
Questions 60 multiple-choice and 5 unscored
Passing Score 68%
Cost $200 USD
Delivery Proctored online or at a testing center
Prerequisites None
Recommended Experience Minimum 1 year of experience in CRM Analytics domains

🎯 Who Should Take This – The Data Architect: You understand how to bridge the gap between raw Salesforce objects and optimized columnar datasets for high-performance querying.

  • The BI Consultant: You have a knack for translating complex business requirements into actionable dashboards that users actually enjoy using.
  • The AI Strategist: You are ready to move beyond descriptive analytics and use Einstein Discovery to provide prescriptive recommendations to stakeholders.
  • The Solution Designer: You know how to implement robust security models and deploy complex analytics assets across multi-org environments.

What You’ll Prove

This credential validates your ability to design and implement a full-stack analytics solution within the Salesforce ecosystem. You aren’t just making charts; you are building a data-driven culture by ensuring data integrity, security, and predictive accuracy. – You can design scalable data architectures using Dataflows and Recipes to join disparate data sources.

  • You can implement complex security protocols including Security Predicates and Sharing Inheritance.
  • You can build advanced visualizations using SAQL and dynamic bindings for highly interactive user experiences.
  • You can deploy AI models via Einstein Discovery stories to predict outcomes and suggest improvements directly on records.
  • You can manage the lifecycle of analytics assets through auditing, performance tuning, and structured deployment processes.

Exam Outline

Domain Weight What’s Covered
Data Layer 24% Dataflow vs Recipe nodes, data sync, external data ingestion, and dataset management.
Analytics Dashboard Design 19% Visualization best practices, chart selection, and XMD modifications for appearance.
Einstein Discovery Story Design 19% Outcome variables, descriptive/predictive insights, and model write-back to Salesforce.
Analytics Dashboard Implementation 18% SAQL query syntax, bindings, facets, and embedding dashboards in Lightning pages.
Security 11% Security Predicates, Sharing Inheritance, and Integration vs Security user roles.
Administration 9% App sharing, Change Sets for deployment, and performance monitoring via Dashboard Inspector.

💡 In Notion, convert each domain row into a toggle to nest your study notes underneath.


Suggested Study Path

  1. Review the core architecture by contrasting the JSON-based Dataflow nodes (augment, flatten, digest) with the visual ETL capabilities of Data Prep Recipes.
  2. Master the security model by practicing the implementation of row-level security through Security Predicates that reference User Attribute fields.
  3. Get hands-on with SAQL to understand how to manually edit dashboard JSON for advanced filtering logic that standard faceting cannot handle.
  4. Complete the Superbadges specifically the CRM Analytics Specialist and Einstein Discovery Story Design badges to validate your readiness.
  5. Study the Einstein Discovery lifecycle from selecting an outcome variable to interpreting the GINI coefficient and deploying the model to production.
  6. Simulate a deployment by using Change Sets or the CLI to move apps and datasets, paying close attention to which elements do not migrate automatically.

⚠️ Watch Out For – Currency conversion logic: Remember that currency values usually display in the Integration User currency unless specific conversion logic is applied.

  • Big Object limitations: Be aware that incremental data sync is not supported for Salesforce Big Objects, which can impact performance for large datasets.
  • Sharing Inheritance boundaries: Don’t assume it works for every object; know the limits and when you must fallback to a manual Security Predicate.
  • Mobile Layout hierarchy: Understand how the system selects a layout when multiple are eligible—it’s often based on the most device properties set.
  • SAQL syntax nuances: Watch out for the specific clauses like foreach, group, and limit that appear in the exam’s code-snippet questions.

🔗 Resources – Official Exam Guide


Data is only as good as the decisions it drives. Go build something that makes your users look like geniuses.

Official status sources

Catalog status last verified: 2026-07-19.