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| Section | Weight | Objectives |
|---|---|---|
| Visualizations & Dashboards | 15% | - Visualization and Dashboard Design
|
| Agentic Experiences | 25% | - Generative AI
|
| Data Setup | 20% | - Data Architecture and Processing
|
| Basic Setup & Admin | 10% | - Agentic Analytics
|
| Managing Workspaces & Orgs | 10% | - Personal Org
|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Tableau Next Apps and Marketplace
|
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NEW QUESTION # 18
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 # 19
The client wants AI-generated insights about Gross Margin % in Tableau Next. Where is the best place to define this context for the agent?
Answer: C
Explanation:
For agent-specific business context about how Gross Margin % should be understood or interpreted, Business Preferences are the best choice. Salesforce uses Business Preferences to add organization-specific knowledge and instructions to a semantic model so Tableau Agent can interpret users' analytical questions according to the organization's terminology and business logic.
A calculated field is appropriate when Gross Margin % itself must be mathematically derived-for example, (Revenue - Cost) / Revenue. However, the question does not ask where to implement the mathematical calculation; it asks where to define context for AI-generated insights. Contextual instructions, such as what
"healthy gross margin" means or which business interpretation to apply, belong in Business Preferences.
A dashboard-scoped calculated field is even less suitable because it confines logic to a specific downstream analytical artifact instead of enriching the governed semantic context used by Tableau Agent across conversational experiences.
Salesforce's broader semantic architecture reinforces this separation: semantic models provide standardized business logic and definitions, while Business Preferences augment those models with business-specific interpretive knowledge for conversational analytics.
References/Topics: Agentic Experiences - > Business Preferences - > Tableau Agent Context - > Semantic Model Enrichment.
NEW QUESTION # 20
During a discovery call, a client tells their Tableau Next Consultant that they love the idea of embedding the Analytics and Visualization Agent into an external portal, but that they have three dashboards on the same page: Sales Performance, Risk Exposure, and Regional Revenue. What is true about the agent's capabilities in this scenario?
Answer: B
Explanation:
The Tableau Next Analytics Embedding SDK supports an AnalyticsAgent component with both single- context and multi-component operating modes. In Multi-Component mode, the application omits the contextConfig property. The agent then automatically tracks the embedded AnalyticsDashboard and AnalyticsMetric components present on that page.
Therefore, B directly describes the intended architecture for a portal containing multiple analytical components.
Option A describes single-context mode, where contextConfig explicitly binds the agent to one dashboard, metric, or semantic model. That mode exists but is not a platform limitation. Option C introduces a same- semantic-model restriction that the current Embedding SDK documentation does not impose. The SDK explicitly describes automatic context tracking across embedded dashboard and metric components.
This capability is particularly important in embedded analytics because it allows conversational analytics to understand the broader analytical surface rather than forcing the external application to continually rebind the agent as users move between embedded components.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next Embedding SDK - > AnalyticsAgent - > Multi-Component Mode.
NEW QUESTION # 21
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 # 22
A financial services firm requires its Analytics Agent to consistently provide concise responses and format all currency outputs in Great British Pounds (GBP). Where should a Tableau Next Consultant configure these global formatting and output style rules?
Answer: B
Explanation:
Business Preferences are the semantic-model mechanism for supplying organization-specific instructions and contextual guidance to Tableau Agent. They can define how the analytics agent should interpret business concepts, terminology, and preferred response conventions. Salesforce recommends keeping each Business Preference short, focused, and high-value because these instructions are added to the agent's prompt.
Accordingly, preferences such as "Use GBP when presenting monetary values" or "Keep responses concise" belong in Business Preferences rather than individual field descriptions. A field description explains what a particular semantic field means; it is not the proper location for broadly applicable output behavior. The Einstein Trust Layer addresses AI trust, security, privacy, and governance controls rather than organization- specific response formatting.
References/Topics: Agentic Experiences - > Business Preferences - > Organizational Terminology - > Response Guidance - > Semantic Model Context.
NEW QUESTION # 23
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