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| Section | Weight | Objectives |
|---|---|---|
| Managing Workspaces & Orgs | 10% | - Workspace and Asset Management
|
| Agentic Experiences | 25% | - Analytics Agent
|
| Basic Setup & Admin | 10% | - User Access
|
| Data Setup | 20% | - Data 360
|
| Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Tableau Next Apps and Marketplace
|
>> New Analytics-Con-202 Exam Questions <<
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NEW QUESTION # 73
A Tableau Next Consultant has completed all the required Salesforce setup steps for Agentforce for Analytics in Slack. However, when the consultant tests it in Slack, they're not seeing the Agentforce icon on a Tableau Next metric card. The consultant confirms that the agent is built from the Analytics and Visualization template and uses the Data Analysis subagent. What is an additional criteria that must be met for the icon to appear?
Answer: C
Explanation:
The Analytics and Visualization Agent must be installed in Slack and enabled for the workspace. Creating the agent from the correct template and including the Data Analysis subagent is necessary, but those steps alone do not expose the conversational experience on Slack metric or dashboard cards.
Salesforce documents several criteria that Slack checks before displaying the Ask Agentforce for Analytics capability. The qualifying Analytics and Visualization agent must be installed and enabled in the Slack workspace, use the Data Analysis subagent, originate from the same Salesforce org as the shared Tableau Next asset, and be accessible to the user through the relevant agent permissions.
A Personal Org is not required; in fact, conversational analytics has specific Personal Org limitations. Nor must an administrator initiate Tableau Agent on behalf of ordinary users. Properly licensed and authorized users can invoke it themselves.
This question tests the distinction between configuring an agent inside Salesforce and actually making that agent available through an external collaboration surface such as Slack.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Integrate Analytics Across Platforms -
> Tableau Next in Slack - > Enable Tableau Agent in Slack.
NEW QUESTION # 74
During agent testing, a Tableau Next Consultant asks, "Who are the top-performing AEs?" and the Tableau Agent returns results based on opportunity count, when the business definition of "top-performing" is based on annual contract value (ACV). Which configuration change best resolves this issue?
Answer: A
Explanation:
This is a textbook use case for Business Preferences. Salesforce defines Business Preferences as business- specific instructions stored within the semantic model that tell Analytics Q & A how to interpret an organization's terminology, defaults, jargon, and business logic.
The expression "top-performing" is ambiguous in ordinary language. The organization has explicitly defined it to mean performance ranked by Annual Contract Value. A Business Preference such as "When users ask about top-performing AEs, use ACV to determine performance" supplies precisely that missing business context.
Renaming ACV to Performance would reduce semantic clarity and distort the actual meaning of the field.
ACV should retain its authoritative business name.
A Verified Question can help calibrate frequently asked questions and improve responses to semantically similar queries, but the underlying issue here is a reusable business-language interpretation rule, not merely one incorrect Q & A example. Business Preferences are therefore the more appropriate semantic mechanism.
Salesforce also recommends keeping Business Preferences concise and using them for contextual interpretation rather than structured calculations that belong in calculated fields or metrics.
References/Topics: Agentic Experiences - > Business Preferences - > Business Terminology - > Analytics Q
& A Accuracy.
NEW QUESTION # 75
During a Tableau Next implementation, a Tableau Next Consultant is explaining to the admin team when Agent Scoping for Tableau Agent actually takes effect. When is Agent Scoping used?
Answer: C
Explanation:
Agent Scoping is specifically designed for situations in which Tableau Agent receives a question without clear analytical context. Salesforce defines Agent Scoping as the administrator-controlled list of semantic models that Tableau Agent can search when context cannot otherwise determine which model should answer the user's question.
Typical examples include Tableau Agent being used in Slack or embedded on a page that does not contain a Tableau Next dashboard, metric, or other asset capable of supplying context. The configured semantic-model list serves as a fallback list. Tableau Agent can then determine which approved model should be used to resolve the user's request.
Agent Scoping does not run indiscriminately for every question, which eliminates B. When Tableau Agent is invoked from an analytical surface that already provides clear semantic context, that existing context guides the interaction. C is also overly restrictive; Agent Scoping is not limited to metric-details pages or scenarios involving multiple models attached to a metric.
Administrators can configure approved fallback semantic models for active Analytics and Visualization agents using the Data Analysis subagent.
References/Topics: Agentic Experiences - > Tableau Agent - > Agent Scoping - > Fallback Semantic Models
- > Context Resolution.
NEW QUESTION # 76
Universal Containers is concerned about Personally Identifiable Information (PII) being exposed when using Data Connection and Analytics Creation capabilities to create calculated fields. How does Data Connection and Analytics Creation ensure data security when processing requests through the large language model (LLM)?
Answer: B
Explanation:
The correct security mechanism is the Einstein Trust Layer's PII masking capability. Salesforce guidance for AI-assisted calculated-field creation states that the agent may use information from the semantic model, including its schema and metadata, and that personally identifiable information is masked by the Einstein Trust Layer before information is sent to the LLM.
This allows Tableau Next's generative functionality to receive the semantic context required to construct useful calculated fields while applying Salesforce's enterprise AI security controls.
Option A describes a whole-model encryption/decryption workflow that is not the documented Tableau Next processing model. Option C is also incorrect because the system does not simply prohibit every field that could potentially contain PII. Instead, the Trust Layer applies masking and other controls to protect sensitive information while retaining useful analytical context.
More broadly, Salesforce states that Tableau Agent and Agentforce inherit the Einstein Trust Layer's security, governance, and trust mechanisms, including protections designed to prevent customer data from being retained by external LLMs for model training.
References/Topics: Agentic Experiences - > Einstein Trust Layer - > PII Masking - > Generative AI Calculated Fields.
NEW QUESTION # 77
Which statement accurately describes a parameter within a Tableau Next semantic model?
Answer: B
Explanation:
A parameter is a user-controllable variable that can influence calculations, filtering, reference lines, and other interactive analytical behavior. Salesforce documents parameters as a mechanism for modeling scenarios and allowing dashboard users to provide inputs that affect analytical results. Parameters can be created for different data types and then referenced by calculated fields or dashboard controls.
For example, an organization could define a parameter named Target Discount and allow a user to enter 15%.
A calculated field could then compare actual discount values with the parameter and dynamically change the resulting visualization. Tableau Next also supports parameter widgets that accept manually entered values or derive dynamic values from dashboard queries.
Option B incorrectly describes semantic-model relationship configuration. Relationships between DMOs are defined through relationship metadata and cardinality rather than parameters. Option C confuses parameters with governance and authorization controls.
The certification distinction is: parameters provide variable analytical input; calculated fields consume that input; semantic relationships define object connectivity; Data 360 governance controls security.
References/Topics: Data Setup - > Semantic Models - > Parameters - > Calculated Fields - > Interactive Scenario Modeling.
NEW QUESTION # 78
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Practicing with Salesforce Analytics-Con-202 Exam questions will help you to become an expert in and acquire the Salesforce Analytics-Con-202. Salesforce Analytics-Con-202 Exam Questions allow you to verify your skills as a professional. You have to pass the Salesforce Analytics-Con-202 to achieve the associate-level certification.
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