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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Setup | 20% | - Data Architecture and Processing
|
| Topic 2: Managing Workspaces & Orgs | 10% | - Workspace and Asset Management
|
| Topic 3: Embedding, Cross-Cloud, & Interoperability | 20% | - Developer Tools and APIs
|
| Topic 4: Agentic Experiences | 25% | - Analytics Agent
|
| Topic 5: Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Topic 6: Basic Setup & Admin | 10% | - Agentic Analytics
|
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NEW QUESTION # 74
A new analyst at Coral Cloud Resorts is responsible for the complete setup of Tableau Next. This includes configuring the platform, managing all users, and overseeing all workspaces and assets. Which permission set must a Tableau Next Consultant assign to the analyst?
Answer: C
Explanation:
Tableau Unmetered Admin is the correct permission set because the user needs full Tableau Next administrative capability rather than analytical authoring alone. Salesforce states that Tableau Unmetered Admin permits access to Tableau Next Setup and edit capabilities across Tableau Next features in the production environment. Administrative users can configure the product and provision users with appropriate Tableau Next permission sets.
Salesforce specifically requires Tableau Unmetered Admin or Tableau Next Admin to access Tableau Next Administration and enable Tableau Next. When Tableau Next is enabled, the administrator also receives the associated Data Cloud Architect capabilities required for underlying Data 360 configuration.
The Platform Analyst role is intended primarily for creating, managing, and sharing governed Tableau Next analytical assets. It does not represent the full administrative persona required to configure Tableau Next and manage users. Self-Service Analyst focuses primarily on Personal Org and self-service analytical workflows and is even further removed from the stated administration requirement.
This question follows least-privilege role design: administrative tasks require the Admin persona; content creation alone generally requires an Analyst persona.
References/Topics: Basic Setup and Admin - > Tableau Next Permission Sets - > Tableau Unmetered Admin
- > User Management - > Tableau Next Setup.
NEW QUESTION # 75
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: A
NEW QUESTION # 76
A Tableau Next Consultant wants to enable conversational analytics for marketing data stored in Snowflake.
What is required?
Answer: A
Explanation:
Tableau Agent's conversational analytics depends on an AI-ready Tableau semantic model, making A correct.
Salesforce positions Tableau Semantics as the governed business layer between connected Data 360 sources and analytical or AI consumption experiences. Semantic models define standardized measures, dimensions, relationships, calculations, metrics, terminology, and business context that Tableau Agent uses to interpret natural-language questions.
For Snowflake data, the consultant establishes an appropriate Data 360 connection-including supported zero- copy federation where appropriate-and exposes the required Snowflake data through Data 360. The consultant then builds and prepares a semantic model containing the marketing concepts that Tableau Agent must analyze. Salesforce's Tableau Agent implementation guidance explicitly requires determining the required data, connecting it through Data 360, and creating suitable semantic foundations before configuring conversational analytics.
CSV export is unnecessary and creates an avoidable duplicate dataset. Building dashboards directly in Snowflake also does not establish Tableau Agent's governed semantic context.
The architecture is therefore: Snowflake - > Data 360 connectivity - > Tableau Semantic Model - > Tableau Agent - > Conversational Analytics.
References/Topics: Data Setup - > Snowflake Integration - > Data 360 - > Tableau Semantics - > AI-Ready Semantic Models.
NEW QUESTION # 77
Before launching a dashboard in Tableau Next, a Tableau Next Consultant gives the appropriate team View access to the dashboard's workspace. Which other access consideration should the consultant verify before rolling this dashboard out to end users?
Answer: C
Explanation:
Tableau Next asset sharing and Data 360 data access are separate layers. Granting users Viewer access to a workspace can provide inherited access to its dashboards, visualizations, and semantic models, but it does not automatically grant access to the underlying Data 360 data. Salesforce explicitly states that access to a semantic model requires access to the data space containing the model as well as access to the objects and fields used by that model.
Therefore, C is correct.
End users do not require Edit access to underlying Data 360 objects merely to view dashboard data, making A unnecessarily privileged. Similarly, B is incorrect because Consumer-level permission sets can view Tableau Next assets; Platform Analyst or Self-Service Analyst permissions are not universally required for dashboard consumption.
The architecture can be understood as three layers: license/permission access, Tableau Next asset sharing, and Data 360 data visibility/governance. Successful dashboard rollout requires all applicable layers to authorize the user. Sharing alone cannot override an administrator's data-space, DMO, DLO, field, or policy restrictions.
References/Topics: Managing Workspaces and Orgs - > Asset Sharing - > Data Spaces - > Data 360 Governance - > Semantic Model Access.
NEW QUESTION # 78
A Tableau Next Consultant needs to ensure that metrics created in Tableau Next are consistently defined across multiple business units. Which feature supports this requirement?
Answer: B
Explanation:
Semantic Data Models are specifically intended to establish standardized, reusable definitions for analytical concepts and metrics. Salesforce describes Tableau Semantics as a semantic layer that maps data to familiar business terminology and standardized logic so information can be interpreted consistently across Salesforce.
Semantic models become a single source of truth for metrics, calculations, relationships, dimensions, and other analytical definitions.
Therefore, if several business units must calculate and interpret a metric consistently, the correct architecture is to define that KPI through the governed semantic model rather than recreating logic independently in each dashboard or workspace.
Workspace-level color palettes address visual presentation and branding rather than analytical definitions.
Dashboard templates can standardize dashboard structure and reuse assets, but they do not provide the authoritative semantic definition layer required to guarantee that the same business metric has the same meaning everywhere.
Salesforce explicitly states that semantic models are first-class Salesforce metadata and can power analytics and data-driven experiences throughout Data 360 and Tableau Next. This reusable semantic architecture prevents divergent metric logic from developing between departments.
References/Topics: Data Setup - > Tableau Semantics - > Semantic Data Models - > Metrics - > Standardized Business Logic - > Single Source of Truth.
NEW QUESTION # 79
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