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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Layer	23%	- Data Management & Optimization 1. Implement data modeling and relationships 2. Resolve data sync and refresh issues 3. Optimize dataset performance - Data Sources & Integration 1. Extract, load, and prepare data using Data Manager 2. Define datasets and map Salesforce objects 3. Use Dataflows and Recipes for transformation
Topic 2: Analytics Administration & Deployment	18%	- Implementation & Maintenance 1. Monitor and optimize query performance 2. Manage versioning and deployment 3. Use Dashboard Inspector and Publisher
Topic 3: Einstein Discovery	22%	- Deployment & Usage 1. Monitor and maintain model performance 2. Embed predictions in dashboards and Lightning pages 3. Interpret results and recommendations - Model Building & Configuration 1. Train, evaluate, and refine models 2. Prepare and assess data for modeling 3. Select prediction type: numeric, binary, multi-class
Topic 4: Dashboard Design & Development	25%	- Design Principles 1. Design for mobile and Lightning compatibility 2. Apply best practices for usability and performance - Build & Configure Dashboards 1. Use SAQL for advanced queries 2. Implement bindings, filters, and interactions 3. Create lenses, steps, and visualizations
Topic 5: Security & Access	12%	- Sharing & Permissions 1. Configure app, dataset, and field-level security 2. Implement row-level security and inheritance 3. Manage user and group access

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q78-Q83):

NEW QUESTION # 78
consultant is reviewing a model that is set to maximize the daily sales quantity of consumer products in stores, and they see this recommendation.

Which action should the consultant take?

A. Remove the Store field from the model definition, because that is the recommended action.
B. Verifyclient expectations that Store is a strong predictor for daily sales quantity.
C. Ignore alert; the explanation of variation is only 35%, which is below 50%,

Answer: B

Explanation:
Upon reviewing the data model and noticing the high correlation alert between 'Store' and daily sales quantity, the appropriate action is to verify with the client their expectations regarding the influence of the Store field on daily sales. Here's the rationale:
* Understanding the Role of 'Store' in the Model: Before making any changes to the model, it's crucial to understand whether the 'Store' field is expected to be a strong predictor based on the business context. If the client expects that different stores inherently have different sales volumes due to factors like location, size, or customer base, this correlation may be both meaningful and desired.
* Potential Data Leakage: High correlation warnings can sometimes indicate data leakage, where a predictor (like 'Store') might inadvertently include information about the outcome variable (daily sales quantity). It's essential to verify whether this correlation makes sense logically or if it's skewing the model predictions.
* Client Consultation: Consulting with the client helps ensure that any modeling decisions align with their business knowledge and expectations. It's about validating the model against real-world expectations and ensuring it remains a useful tool for decision-making.
By taking these steps, the consultant not only adheres to best practices in data science by validating model inputs and their implications but also ensures that the model aligns with the client's business strategies and operational realities.

NEW QUESTION # 79
A CRM Analytics consultant is working on Sales dashboards with multiple datasets and advanced queries in the Sales Analytics app.
Sales managers in the organization have been given Editor/Manager access to the app, whereas sales reps have been given Viewer access.
Some dashboards that are in progress are not ready to be rolled out to sales reps and should only be viewable by sales managers.
How should the consultant accomplish this?

A. Remove the dashboard from the 'Run App' navigation list so the sales reps cannot navigate to these dashboards.
B. Duplicate the dashboards and their respective datasets, and move the assets to a separate app for the sales rep.
C. Leverage the CRM Analytics asset visibility feature to hide the assets from the users.

Answer: C

Explanation:
In CRM Analytics, you can control the visibility of dashboards and other assets using theasset visibilityfeature. This allows the consultant to restrict access to specific assets (like dashboards) for certain groups of users, such as sales reps, without needing to duplicate datasets or move dashboards to another app.
This is the most efficient way to manage access for dashboards in progress while allowing only sales managers to view the in-progress dashboards.

NEW QUESTION # 80
The CRM Analytics project team at Universal Containers is creating an app with dashboards, datasets, and lenses. The app has been shared with multiple users with Viewer, Editor, and/or Manager access.
One end user is unable to view the dashboard watchlist that was previously set up. They are receiving a
"Resource not found" error while trying to access the dashboard. The team confirms that the end user has Viewer access to the app but the project team is able to view the dashboard.
What is the reason for this error?

A. The dashboard is deleted by a user with Manager access to the App.
B. The dashboard has been hidden by a user with Manager access to the App.
C. The dashboard or App permission needs to be updated to Editor.

Answer: B

NEW QUESTION # 81
A consultant runs the sharing inheritance coverage assessment for the Opportunity object and finds that some records exceed 400 sharing descriptors.
What should the consultant do?

A. Contact Salesforce Support to increase the sharing descriptor limit.
B. Use security predicates in CRM Analytics.
C. Increase the sharing descriptor limit in the analytics settings.

Answer: B

Explanation:
When a record exceeds 400 sharing descriptors, it can cause performance issues or sharing rule complications in CRM Analytics. In such cases, the recommended solution is to usesecurity predicates, which allow fine- tuned control over which data is visible to users based on their sharing rules and permissions. Security predicates reduce the number of sharing descriptors by enforcing security at the dataset level rather than relying solely on record-sharing mechanisms.
Increasing the sharing descriptor limit is not an available option, and Salesforce Support does not typically increase this limit, making the use of security predicates the best approach.

NEW QUESTION # 82
A CRM Analytics consultant has enabled data sync manually in an org that uses dataflows/recipes. The client says that the dataflow/recipe fails each time it starts running.
What is causing the dataflow/recipe to fail?

A. Dataflows/recipes with Augment nodes fail until sync has run for the first time.
B. Dataflowsysrecipes with computeExpression nodes fail until syne has run for the first time.
C. Dataflows/recipes with sfdcDigest nodes fail until sync has run for the first time.

Answer: C

NEW QUESTION # 83
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