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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Setup | 20% | - Data 360
|
| Topic 2: Embedding, Cross-Cloud, & Interoperability | 20% | - Cross-Platform Workflows
|
| Topic 3: Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Topic 4: Agentic Experiences | 25% | - Agentic Readiness
|
| Topic 5: Managing Workspaces & Orgs | 10% | - Asset Management and Sharing
|
| Topic 6: Basic Setup & Admin | 10% | - Access Management
|
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NEW QUESTION # 71
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: C
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 # 72
Cloud Kicks (CK) uses CRM Analytics (CRMA) for operational embedded reporting within its Agentforce Sales console and Tableau Cloud for historical deep- dive executive dashboards. CK is now evaluating the addition of Tableau Next to its analytics architecture. Which statement accurately describes the distinct positioning benefit of adding Tableau Next to this multi- platform ecosystem?
Answer: B
Explanation:
Tableau Next's distinctive value is its agentic, conversational, and actionable analytics layer, so C is correct.
Salesforce positions Tableau Next as an end-to-end agentic analytics platform combining Tableau analytics, Agentforce AI, and the Data 360 semantic layer. It enables users to ask freeform analytical questions, receive grounded text and visual answers, obtain proactive insights, and initiate actions where work occurs.
The platform is therefore complementary to existing analytical investments. Tableau Cloud can continue supporting sophisticated traditional analytics and executive exploration, while CRM Analytics can continue supporting embedded Salesforce analytical use cases. Tableau Next introduces a governed semantic and agentic layer that makes data conversational and actionable.
Option A is too absolute. Salesforce interoperability capabilities explicitly support connecting Tableau Cloud to Tableau Semantics, illustrating coexistence rather than mandatory replacement. Option B also mischaracterizes Published Data Source integration: Tableau Next can build semantic models directly from supported Tableau Cloud PDS content; its purpose is not merely extraction into DMOs.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next Positioning - > Tableau Agent - > Tableau Cloud and CRM Analytics Coexistence.
NEW QUESTION # 73
A Tableau Next Consultant is configuring a Salesforce action in a Tableau Next table visualization that displays Contact records. The goal is to give sales reps the ability to trigger a screen flow that adds selected Contacts to a Campaign. What is a required configuration step for the action to work correctly?
Answer: C
Explanation:
A Salesforce action executed from a Tableau Next visualization must know which Salesforce record the user is acting upon. Salesforce documentation therefore requires the consultant to select the appropriate record ID when configuring the action. The record ID is the primary identifier for the Salesforce object, and it must be available as part of the visualization. For Contact-based actions, this means mapping the Contact ID so that Tableau Next can invoke the action against the correct Contact record.
The multi-row selection setting in A is not the fundamental record-context requirement for a standard Salesforce action. Likewise, B is misleading. Users certainly require authorization to execute the underlying Salesforce action, but Tableau Next does not require the consultant to create a special Tableau-specific custom permission set merely to map the action.
Architecturally, Tableau Next integrates the analytical and transactional layers by associating visualization data with Salesforce object identifiers. Once a user selects the relevant data element, Tableau Next can pass the corresponding record identity into the configured Salesforce action.
References/Topics: Visualizations and Dashboards - > Add Actions to Visualizations - > Salesforce Actions -
> Record ID Mapping.
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: B
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
A Tableau Next Consultant is asked to configure agent scoping. What is the purpose?
Answer: C
Explanation:
Agent Scoping determines which approved semantic models Tableau Agent can search when a user's question lacks sufficient analytical context. Salesforce describes Agent Scoping as defining a fallback list of semantic models for a particular analytics agent. This fallback is used when Tableau Agent cannot infer the appropriate model from the current page or analytical asset.
Examples include asking Tableau Agent a question from Slack or embedding the agent on a page that contains no Tableau Next metric or dashboard. In those circumstances, the agent uses its approved fallback models to determine the appropriate semantic context.
When a user asks a question from a dashboard or metric that already supplies clear analytical context, Salesforce states that Tableau Agent uses the semantic models associated with that asset instead of the fallback list. User permissions remain enforced at runtime; placing a model on the fallback list never grants unauthorized access.
Option B is incorrect because Agent Scoping does not enforce row-level security; Data 360 governance and user permissions perform that function. Option C is unrelated to agent routing.
References/Topics: Agentic Experiences - > Tableau Agent - > Agent Scoping - > Fallback Semantic Models
- > Context Resolution.
NEW QUESTION # 76
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