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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Agentic Experiences | 25% | - Agentic Readiness
|
| Topic 2: Data Setup | 20% | - Data Architecture and Processing
|
| Topic 3: Embedding, Cross-Cloud, & Interoperability | 20% | - Cross-Platform Workflows
|
| Topic 4: Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Topic 5: Basic Setup & Admin | 10% | - Tableau Next Setup
|
| Topic 6: Managing Workspaces & Orgs | 10% | - Workspace and Asset Management
|
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NEW QUESTION # 23
A Tableau Next Consultant receives a request from a business user to help troubleshoot an issue with setting data alerts using Tableau Agent. The consultant verifies that the business user has been granted a Tableau Next Consumer license and is accessing Tableau Agent from a page with Tableau Next on it. Which reason explains why the business user is unable to set the alert?
Answer: A
Explanation:
The limiting factor in this scenario is the user's license level. Setting proactive data alerts through Tableau Agent is an authoring-oriented capability that requires Tableau Next Creator access. A Consumer user can view and interact with published analytical content, but the Consumer persona does not receive the full set of creation and configuration capabilities needed to define alert conditions.
The fallback semantic model in option B is used when Tableau Agent lacks clear analytical context, such as when a user invokes the agent from a surface that does not already identify the relevant Tableau Next asset.
Here, the user is explicitly accessing Tableau Agent from a page that contains Tableau Next content, so lack of fallback scoping is not the primary issue. Option A can prevent analysis of a particular metric, but the question establishes a broader inability to set the alert and emphasizes that the user has a Consumer license.
The appropriate remediation is therefore to use the Creator-level entitlement for users who must configure proactive alerts. This preserves the distinction between consumption permissions and analytical creation
/configuration permissions.
References/Topics: Agentic Experiences - > Tableau Agent - > Proactive Data Alerts - > Creator Permissions.
NEW QUESTION # 24
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 # 25
A Tableau Next Consultant is asked to configure proactive alerts for metrics. Which prerequisite must be met before alerts can be created?
Answer: B
Explanation:
Inspector Proactive Data Alerts operate against Tableau Next metrics, and Tableau Next metrics are semantic definitions created within the Tableau Semantics layer. Salesforce describes a metric as a governed business KPI derived from measures in a semantic model. Metrics can then support exploration, goals, thresholds, and Inspector alerts.
Therefore, B represents the architectural prerequisite among the supplied options. An alert must have a valid metric whose governed definition provides the measure, aggregation, temporal context, and other analytical semantics Inspector evaluates.
A user does not need to embed the metric in a dashboard. Salesforce's documented alert workflow starts from the Tableau Next metric page, where the user opens Tableau Agent and asks it to create an alert against that metric.
Option A is also not the fundamental prerequisite described by architecture. Although alert-management experiences can be reached through metric-related surfaces, the key technical dependency is the existence of the metric itself.
Current configuration also requires Tableau Agent/Data Analysis and Inspector Proactive Alerts to be enabled administratively. These are environment-level prerequisites, but they are not among the answer choices.
References/Topics: Agentic Experiences - > Inspector Proactive Data Alerts - > Metrics - > Semantic Models - > Data Analysis.
NEW QUESTION # 26
A Tableau Next Consultant has developed a dashboard using a single semantic model. The dashboard includes filters, metrics, and visualizations. The consultant wants to be able to make changes to their filters and selections in their visualizations that update the metrics. They are already able to filter visualizations between each other by clicking into the views and using the filters on the page. What does the consultant need to validate to have the desired functionality?
Answer: A
Explanation:
For a Tableau Next Metric widget to respond dynamically to dashboard filtering, two conditions must be satisfied. First, the metric widget must be configured to receive dashboard filters. Second, the dimensions being used by those dashboard filters must exist in the metric definition as supported dimensions. Salesforce specifically documents that a Metric widget can only be filtered by dimensions explicitly included in the metric definition, typically as Additional Dimensions.
Therefore, C is the only complete answer.
Option A fails because enabling dashboard-filter reception is not enough if the metric definition lacks the necessary dimensions. Tableau Next cannot apply a filter against a dimensional grain the metric does not expose. Option B has the required dimensions but explicitly disables receipt of dashboard filters, preventing the widget from responding to dashboard interactions.
This distinction is important because visualizations and metric widgets have different interaction requirements. A dashboard visualization can participate naturally in interactive filtering, whereas a governed metric must expose the appropriate dimensions in its semantic definition before those dashboard selections can alter the displayed metric result.
References/Topics: Visualizations and Dashboards - > Metric Widgets - > Receive Dashboard Filters - > Metric Additional Dimensions.
NEW QUESTION # 27
A Tableau Next Consultant is adding a field description to a new calculated field. What are characteristics of a good field description?
Answer: A
Explanation:
A high-quality semantic field description should be clear, concise, and business-contextual, making C correct.
Tableau Agent relies heavily on semantic metadata to determine what fields represent, when they should be used, and how they relate to a user's natural-language question.
Salesforce's Tableau Next semantic-model guidance explicitly recommends descriptions that are clear and concise and add context. Effective descriptions explain the field's purpose, business scope, meaning, relevant data behavior, and relationships when appropriate. Salesforce also recommends avoiding vague definitions or descriptions that simply repeat the field label.
Option A overemphasizes length and technical calculation detail. Excessively long descriptions can introduce unnecessary complexity and ambiguity; the objective is useful business meaning, not exhaustive implementation documentation. Option B captures brevity but omits the most important factor: business context.
For example, a field named Net_Revenue is better described as "Revenue from finalized product sales after discounts, returns, and allowances" than merely "Calculated net revenue." The former gives the agent information needed to map business-language requests accurately.
References/Topics: Data Setup - > Semantic Model AI Readiness - > Field Metadata - > Business-Friendly Descriptions.
NEW QUESTION # 28
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