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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Visualizations & Dashboards | 15% | - Visualization and Dashboard Design
|
| Topic 2: Embedding, Cross-Cloud, & Interoperability | 20% | - Developer Tools and APIs
|
| Topic 3: Data Setup | 20% | - Data Architecture and Processing
|
| Topic 4: Basic Setup & Admin | 10% | - User Access
|
| Topic 5: Agentic Experiences | 25% | - Generative AI
|
| Topic 6: Managing Workspaces & Orgs | 10% | - Workspace and Asset Management
|
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NEW QUESTION # 62
A Tableau Next Consultant is asked to configure workspace access for sensitive dashboards. Which General Access setting ensures no one can see dashboards by default?
Answer: B
Explanation:
Restricted is the correct General Access state. Salesforce documents that newly created Tableau Next assets are restricted by default. When General Access remains restricted, only individual users or Analytics Groups that have been explicitly granted access can open the asset.
For sensitive dashboards, this provides the correct baseline because access is opt-in rather than org-wide. The owner can then grant specific users or groups Viewer access and, where supported at the workspace level, Editor access.
Salesforce also makes an important distinction between Tableau Next asset access and underlying data access.
Even if a dashboard is shared with a user, that action does not automatically grant permission to the DLOs, DMOs, or data spaces on which the dashboard depends. Data 360 governance still applies separately.
"Public" and "Shared" are not the documented General Access states that produce the required private-by- default behavior. Current Tableau Next access management uses Restricted as the state in which only explicitly shared users or groups can access an asset.
For sensitive content, the architecture should therefore use Restricted asset access + explicit user/group sharing + Data 360 governance.
References/Topics: Managing Workspaces and Orgs - > General Access - > Restricted - > Asset Sharing - > Data Governance.
NEW QUESTION # 63
A Tableau Next Consultant has shared a workspace with a group of users and granted them Editor access at the workspace level. However, one of the users reports that they are still unable to edit a dashboard within that workspace. What is the most likely reason for this issue?
Answer: A
Explanation:
Tableau Next applies both asset-sharing permissions and platform permission sets. Granting Editor access through workspace sharing cannot elevate a user's capabilities beyond those granted by the administrator.
Salesforce explicitly states that sharing doesn't override permissions set by the admin and that a user who lacks the permission set required to edit Tableau Next assets cannot edit an asset even when granted Editor access.
Therefore, C is correct.
Workspace-level access is designed to simplify administration. Users and Analytics Groups can be granted Viewer or Editor access to a workspace, with appropriate access applying to contained assets subject to underlying security and permission requirements. Consequently, B is incorrect as a general explanation.
Option A is also incorrect. Workspace owners can share assets subject to their own permissions, but inability of the affected user to edit is not because dashboards universally require a separate owner-assigned Editor permission.
Think of Tableau Next authorization as multiple gates: license - > Tableau Next permission set - > asset sharing - > underlying data access. A more permissive setting at a downstream sharing layer cannot bypass a restrictive upstream administrative permission.
References/Topics: Managing Workspaces and Orgs - > Workspace Sharing - > Editor Access - > Tableau Next Permission Sets - > Permission Inheritance.
NEW QUESTION # 64
What is a prerequisite for using generative AI to create calculated fields using multi- turn, natural language?
Answer: C
Explanation:
Option A, Draft with Einstein, can generate a calculation from natural language, but the question specifically asks about the multi-turn conversational agent experience, where the agent interacts with the user and refines the requirement. Therefore it is not the best answer. Option B addresses optimization/readiness rather than calculated-field authoring.
References/Topics: Agentic Experiences - > Tableau Agent - > Semantic Modeling/Data Pro - > Conversational Calculated Fields - > Natural-Language Authoring.
NEW QUESTION # 65
A Tableau Next Consultant successfully creates a calculated field using Data Connection and Analytics Creation Subagent involving a Sales data model object (DMO) and Customer DMO. However, when attempting a similar calculation involving a Territory DMO, Data Pro fails. What is the most likely cause?
Answer: A
Explanation:
Data Pro-now increasingly referred to under Semantic Modeling functionality-depends on relationships already defined between the data model objects participating in a generated calculated field. Salesforce explicitly states that a predefined relationship must exist between DMOs for Data Pro to create a calculated field spanning those objects. The agent cannot construct a valid cross-object calculation when the required relationship does not exist.
Therefore, if calculations involving Sales and Customer work but introducing Territory causes the operation to fail, the most likely issue is that Territory is not relationally connected to the relevant objects.
Good metadata and field descriptions improve semantic clarity and AI accuracy, but insufficient descriptions are not the hard technical prerequisite being tested. Likewise, Salesforce does not document a general two- DMO maximum corresponding to option C.
The broader architectural principle is that generative semantic-model functionality does not replace proper data modeling. AI features consume the semantic model's existing object structure, metadata, and relationships. Consultants must establish valid relationships before expecting Tableau Agent to synthesize calculations involving fields from multiple objects.
References/Topics: Data Setup - > Semantic Models - > DMO Relationships - > AI-Generated Calculated Fields - > Data Pro/Semantic Modeling.
NEW QUESTION # 66
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
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 # 67
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