Analytics-Con-201
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Analytics-Con-201 is for the Salesforce Certified CRM Analytics and Einstein Discovery Consultant exam. Salesforce's official exam guide names the certification but does not display Analytics-Con-201 as an official exam code.
The certification evaluates your ability to design, build, secure, and support CRM Analytics datasets, apps, and dashboards, as well as use Einstein Discovery to develop and evaluate predictions.
Page Contents
- Exam Overview
- Exam Information
- Target Audience
- Skills Measured
- Preparation Priorities
- Common Preparation Mistakes
- Frequently Asked Questions
- Study Materials
- Disclaimer
Exam Overview
This consultant exam covers more than dashboard creation. You need to understand how data enters CRM Analytics, how datasets are prepared and secured, how dashboards turn business requirements into useful analysis, and how Einstein Discovery models are evaluated and used in Salesforce.
Salesforce recommends a combination of hands-on experience and self-study. Its candidate profile describes a consultant with at least one year of experience across CRM Analytics and Einstein Discovery. The exam assesses Salesforce Lightning Experience.
Exam Information
| Exam Item | Details |
| Official Certification Name | Salesforce Certified CRM Analytics and Einstein Discovery Consultant |
| Page Product Identifier | Analytics-Con-201; not confirmed as an official Salesforce exam code |
| Exam Questions | 60 scored multiple-choice questions; up to 5 additional unscored questions may appear |
| Time Limit | 90 minutes |
| Passing Score | 65% |
| Registration Fee | $200 USD or ¥30,000 JPY, plus applicable taxes |
| Retake Fee | $100 USD or ¥15,000 JPY, plus applicable taxes |
| Delivery | Proctored online or at a testing center |
| Prerequisite | None |
Who Should Take This Exam?
The certification is intended for consultants who design and implement CRM Analytics and Einstein Discovery solutions for customers or internal teams. Relevant work includes:
- Loading and transforming data to create reliable datasets
- Managing CRM Analytics apps, access, and dataset security
- Designing dashboards around business questions and user needs
- Building queries and dashboard interactions
- Evaluating Einstein Discovery models and presenting predictions in Salesforce
Salesforce’s candidate profile includes experience with SAQL, dataset management, security predicates, dashboard JSON, dataflows or recipes, and Einstein Discovery stories. It does not expect candidates to write Apex or build integrations with an SDK.
Skills Measured
| Official Domain | Weight | Main Focus |
| Admin/Configuration | 17% | Enable CRM Analytics, assign licenses and permissions, work within platform limits, and deploy between environments. |
| Data Layer | 23% | Extract and load data, build datasets, schedule refreshes, transform data with recipes or dataflows, and manage extended metadata. |
| Security | 16% | Control user and app access; apply sharing inheritance and security predicates for row-level dataset access. |
| Analytics Dashboard Design | 13% | Gather requirements, choose suitable visualizations, apply UX principles, and assess templated apps. |
| Analytics Dashboard Implementation | 19% | Configure queries and widgets, create dashboard interactions, use advanced calculations, embed dashboards, and inspect performance. |
| Einstein Discovery | 12% | Select prediction types, assess model results, improve input data, deploy predictions, and monitor model performance. |
Preparation Priorities
Start with the Data Layer
At 23%, Data Layer is the largest domain. Practise creating datasets from source data, choosing between recipes and dataflows, managing refresh schedules, and checking the effect of data sync and platform limits.
Build Dashboards from Requirements
Dashboard Design and Dashboard Implementation together account for 32%. Practise choosing visualizations, writing or selecting queries, connecting widgets through interactions, embedding dashboards in Lightning pages, and using Dashboard Inspector when performance declines.
Test Security with Different Users
App sharing and dataset row access solve different problems. Verify a solution from the perspective of users with different permissions rather than assuming that access to an app grants access to every record.
Interpret Einstein Discovery Results
Know how to choose a prediction type, assess whether the underlying data supports the business question, read model results, and decide what to change before deploying a prediction.
Common Preparation Mistakes
Designing a Dashboard Before Checking the Data
A dashboard cannot fix missing fields, poor joins, or an unsuitable refresh schedule. Confirm that the dataset supports the intended calculations and level of detail first.
Confusing Dashboard Access with Row-Level Security
Sharing an app controls who can open its assets. Security predicates and sharing inheritance control which dataset rows a user can see.
Choosing a Visualization Because It Looks Familiar
Start with the question the user needs to answer: comparison, trend, distribution, or detailed investigation. Then choose the visualization and interaction that make that answer clear.
Optimizing Queries Without Measuring the Problem
When a dashboard is slow, use Dashboard Inspector to locate the expensive step. Rewriting every query without evidence can create extra work and new errors.
Treating a Prediction as Automatically Useful
A model result must be interpreted in business context. Check data quality, model performance, and how the prediction will be surfaced to users before recommending deployment.
Frequently Asked Questions
Do I need to be a Salesforce developer?
No. The official candidate profile does not require Apex coding or SDK development. You do need to understand CRM Analytics queries, configuration, data preparation, security, and dashboard implementation.
What is the best hands-on practice?
Build a small solution from start to finish: load and transform data, create a dataset, apply security, build an interactive dashboard, test it as different users, and inspect its performance.
How should I prepare for Einstein Discovery?
Practise selecting a prediction type, reviewing story and model results, identifying weak input data, and deciding whether a prediction is ready to appear on a Lightning record page.
Which official learning resources should I use?
Salesforce recommends its CRM Analytics and Einstein Discovery Trailhead content and certification Trailmix.
How do I maintain the certification?
Salesforce requires certification holders to complete applicable maintenance by the published deadline.
Analytics-Con-201 Study Materials
CertQueen Analytics-Con-201 preparation materials are organized around the six domains in the Salesforce CRM Analytics and Einstein Discovery Consultant exam guide.
- Review of data ingestion, datasets, recipes, dataflows, and refreshes
- Practice with app access, security predicates, and sharing inheritance
- Coverage of dashboard requirements, queries, interactions, and performance
- Review of Einstein Discovery model evaluation and prediction use cases
- PDF and practice-software options where listed on the product page
- 12 months of free content updates, with an optional upgrade to 24 months for $10
The standard package includes 12 months of free content updates from the purchase date. Customers can extend the update period to 24 months for an additional $10. Check the selected product option for its included formats and access terms.
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Disclaimer
CertQueen is an independent exam-preparation provider and is not affiliated with or endorsed by Salesforce. Exam details and maintenance requirements can change. Salesforce, CRM Analytics, Einstein Discovery, and related names are trademarks of their respective owners.