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| Section | Weight | Objectives |
|---|---|---|
| Data Setup | 20% | - Data Architecture
|
| Basic Setup & Admin | 10% | - Agentic Analytics
|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Developer Tools and APIs
|
| Managing Workspaces & Orgs | 10% | - Personal Org
|
| Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Agentic Experiences | 25% | - Agentic Readiness
|
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NEW QUESTION # 42
A Tableau Next Consultant interacts with a Tableau Next dashboard and identifies an issue with a Tableau Next metric: It's using the wrong date field to trend the measure field. The consultant has confirmed that the correct date field exists within the semantic model. How should the consultant update the Tableau Next metric?
Answer: A
Explanation:
The consultant should modify the metric definition in the underlying semantic model. Tableau Next metrics are semantic-layer objects. Salesforce defines a metric as a business KPI derived from one or more measures together with a date field, and metrics are built from semantic models.
Therefore, selecting which date dimension governs the metric's time trend is part of the metric's semantic definition rather than dashboard presentation logic. The dashboard consumes the governed metric; changing the dashboard would not correct the authoritative metric definition.
Option B is also inappropriate. Data Lake Objects and Data Model Objects define the underlying physical
/logical data available in Data 360. Because the correct date field already exists in the semantic model, there is no requirement to modify the underlying DLO or DMO. The problem lies specifically in which existing semantic field the metric uses for its temporal definition.
This reflects a central Tableau Next architectural principle: reusable analytical business logic-including metrics, calculations, temporal semantics, and contextual definitions-should reside in Tableau Semantics, while dashboards remain downstream consumption and presentation layers.
References/Topics: Data Setup - > Semantic Models - > Metrics - > Measure and Date Field Configuration.
NEW QUESTION # 43
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: B
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 # 44
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: B
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 # 45
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 # 46
An Agentforce Sales customer approaches a Tableau Next Consultant asking for analytics on pipeline health and rep performance. They have no existing analytics investment, want minimal setup time, and have no plans to build custom dashboards. What should the consultant recommend to meet this requirement?
Answer: A
Explanation:
The Tableau Next Sales Insights app is specifically designed to provide preconfigured sales analytics covering areas such as sales performance, pipeline health, and related operational sales measures. Salesforce describes Sales Insights as a packaged, data-driven sales solution that combines Tableau Next dashboards and analytics with Salesforce customer and sales data. It is intended to accelerate deployment rather than requiring organizations to design an analytics architecture from the ground up.
That positioning matches every constraint in the scenario: the organization already uses Agentforce Sales, has no existing analytics investment, wants minimal implementation effort, and does not intend to develop custom dashboards.
A custom Lightning Web Component would increase development, testing, governance, and maintenance effort. Full Tableau Next Creator licenses would give users broader authoring functionality than the stated requirement demands and would still leave the organization responsible for creating the analytical content itself.
Sales Insights also includes packaged semantic models, data objects, metrics, and dashboards, which substantially reduces the configuration burden compared with a greenfield Tableau Next implementation.
References/Topics: Basic Setup and Admin - > Tableau Next Sales Insights - > Packaged Analytics - > Agentforce Sales Integration.
NEW QUESTION # 47
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