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| Section | Weight | Objectives |
|---|---|---|
| Basic Setup & Admin | 10% | - Tableau Next Activation and Management
|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Cross-Platform Workflows
|
| Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Managing Workspaces & Orgs | 10% | - Asset Deployment
|
| Data Setup | 20% | - Semantic Models
|
| Agentic Experiences | 25% | - Generative AI
|
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NEW QUESTION # 20
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 # 21
A Tableau Next Consultant has created a new semantic model and wants to identify potential metadata gaps that might confuse the Analytics Agent. Which tool provides an automated "Readiness Score" and actionable suggestions to improve the model's clarity for the AI?
Answer: B
Explanation:
Optimize Model is the feature designed to assess semantic models for AI readiness and recommend improvements. Salesforce describes Semantic Model AI Optimization as evaluating model quality, diagnosing problems, and supplying guided remediation that improves reliability for Tableau Agent. After the feature is enabled, an Optimize Model indicator appears in Semantic Model Builder and shows the model's AI-readiness strength.
Opening the Optimize Model panel provides a breakdown of AI-readiness indicators together with recommended corrective actions. The rating is recalculated as the semantic model changes, allowing consultants to iteratively improve metadata, structure, and agent compatibility.
Q & A Calibration serves a different purpose: it tests representative natural-language questions and helps calibrate how Tableau Agent responds. Business Preferences provide explicit business context and rules, such as how ambiguous terminology should be interpreted. Neither performs the automated holistic readiness evaluation described in the question.
References/Topics: Data Setup - > Semantic Model AI Optimization - > Optimize Model - > AI-Readiness Strength - > Recommended Actions.
NEW QUESTION # 22
Cloud Kicks (CK) has created Tableau Next dashboards and visualizations in a sandbox. These assets rely on new semantic models also developed in the same sandbox. CK's Tableau Next Consultant plans to use a data kit to deploy all assets to the production org. During the data kit creation process, they added the dashboards and visualizations. Which step must the consultant perform to ensure the deployment succeeds?
Answer: C
Explanation:
When Tableau Next assets and their semantic-model dependencies are deployed through a Data Kit, the consultant must explicitly review and correct the publishing sequence. Salesforce documents a minimum dependency sequence of Semantic Models - > Workspaces - > Visualizations - > Dashboards. This ordering is mandatory because visualizations depend on both semantic models and workspaces, while dashboards depend on their visualizations. Salesforce specifically warns that deployment can fail if the publishing sequence isn't reviewed and updated appropriately.
Selecting DevOps is part of creating the deployment Data Kit, but it does not automatically resolve every dependency sequence, making B insufficient. Salesforce notes that the default sequence can be based on asset creation dates and therefore might not match the required dependency order. A is also incorrect because semantic models and Tableau Next assets can be included in a Data Kit deployment to a production home org; deploying the semantic model separately through a change set is not the required approach.
References/Topics: Managing Workspaces and Orgs - > Data Kits - > DevOps Deployment - > Publishing Sequence - > Dependency Management.
NEW QUESTION # 23
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: C
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 # 24
A Tableau Next Consultant is asked to configure Slack integration for proactive alerts. Which setup step is required?
Answer: B
Explanation:
The administrator must enable Collaborate with Slack and Tableau Next, making A correct. Salesforce's documented setup requires connecting the Salesforce org to Slack and then navigating to Tableau Next Administration settings to confirm that Collaborate with Slack and Tableau Next is enabled.
For Inspector Proactive Data Alerts specifically, Salesforce states that Slack must first be enabled for Tableau Next. Users can then receive Inspector alerts through Slack after the Agentforce app and associated connection are configured.
Option B is not the documented prerequisite. Tableau Next relies on appropriate Tableau Next permissions plus Salesforce/Slack identity and connection configuration; assigning a generic "Slack User" permission set is not the required answer.
Option C is also inaccurate as written. A properly configured Analytics and Visualization agent must contain the relevant Data Analysis and Data Alert Management capabilities, but administrators do not necessarily need to create an entirely new agent solely because Slack is being enabled; an existing qualifying agent can be configured and activated.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next with Slack - > Inspector Alerts - > Collaboration Settings - > Agentforce App.
NEW QUESTION # 25
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