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| Section | Weight | Objectives |
|---|---|---|
| Plan and Prepare Data Connections | 22% | - Design row-level security (RLS) and advanced connections
|
| Establish Governance and Support Published Content | 16% | - Deploy and manage content lifecycle
|
| Design and Troubleshoot Calculations and Workbooks | 40% | - Implement and optimize calculations
|
| Evaluate Current State | 22% | - Evaluate current data structures
|
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NEW QUESTION # 28
A Tableau Next Consultant is asked to configure row-level security (RLS) for sensitive HR data. Where should this be defined?
Answer: C
Explanation:
Row-level security for this scenario should be defined in the semantic model so the governed analytical layer determines which records each user is allowed to retrieve. By applying RLS at the semantic-model level, the access rule travels with the analytical definitions used by metrics, visualizations, dashboards, and agentic experiences instead of depending on a particular dashboard layout.
Dashboard filters and visualization properties are presentation controls. They can alter what appears on a given screen, but they are not an appropriate substitute for a security rule because a user could potentially access the same underlying semantic content through another approved analytical surface. The restriction therefore belongs in the model that governs how analytical queries resolve against the sensitive HR dataset.
For an HR scenario, the RLS rule can be based on attributes such as employee, manager, department, region, or another authorized access dimension. The objective is to ensure that every downstream analytical experience receives only the rows permitted for the signed-in user. This centralizes security behavior and reduces the risk of inconsistent filtering across dashboards.
References/Topics: Data Setup - > Semantic Models - > Row-Level Security - > Governed HR Data.
NEW QUESTION # 29
A Tableau Next Consultant is asked to configure semantic models for sales and service data. What is the benefit of semantic models?
Answer: C
Explanation:
The fundamental purpose of Tableau Semantics is to establish consistent, governed business definitions that can be reused across analytical and AI experiences. Salesforce describes semantic models as the place where organizations define and govern business metrics, relationships, dimensions, calculations, and familiar business terminology.
This means sales and service teams can use the same authoritative definitions rather than implementing independent calculations within each dashboard. For example, concepts such as Annual Recurring Revenue, Case Resolution Time, Customer Lifetime Value, or Gross Margin can be defined centrally and then reused across dashboards, metrics, Tableau Agent conversations, and other Data 360-powered experiences.
Option B is far too narrow. Semantic models can support efficient query generation, but their primary benefit is not merely dashboard rendering performance.
Option C is also incorrect. Tableau Next inherits RLS and other governance controls from Data 360 security policies; a semantic model does not automatically create record-level security simply by existing.
The exam principle is: Tableau Semantics = reusable, centrally governed meaning, ensuring humans, dashboards, metrics, and AI reason from the same business definitions.
References/Topics: Data Setup - > Tableau Semantics - > Semantic Models - > Single Source of Truth - > Standardized Business Logic.
NEW QUESTION # 30
A Tableau Next Consultant is asked to configure agent scoping. What is the purpose?
Answer: B
Explanation:
Agent Scoping determines which approved semantic models Tableau Agent can search when a user's question lacks sufficient analytical context. Salesforce describes Agent Scoping as defining a fallback list of semantic models for a particular analytics agent. This fallback is used when Tableau Agent cannot infer the appropriate model from the current page or analytical asset.
Examples include asking Tableau Agent a question from Slack or embedding the agent on a page that contains no Tableau Next metric or dashboard. In those circumstances, the agent uses its approved fallback models to determine the appropriate semantic context.
When a user asks a question from a dashboard or metric that already supplies clear analytical context, Salesforce states that Tableau Agent uses the semantic models associated with that asset instead of the fallback list. User permissions remain enforced at runtime; placing a model on the fallback list never grants unauthorized access.
Option B is incorrect because Agent Scoping does not enforce row-level security; Data 360 governance and user permissions perform that function. Option C is unrelated to agent routing.
References/Topics: Agentic Experiences - > Tableau Agent - > Agent Scoping - > Fallback Semantic Models
- > Context Resolution.
NEW QUESTION # 31
A Tableau Next Consultant is asked to configure proactive alerts for metrics. Which prerequisite must be met before alerts can be created?
Answer: C
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 # 32
A Tableau Next Consultant is configuring a Salesforce action in a Tableau Next table visualization that displays Contact records. The goal is to give sales reps the ability to trigger a screen flow that adds selected Contacts to a Campaign. What is a required configuration step for the action to work correctly?
Answer: C
Explanation:
A Salesforce action executed from a Tableau Next visualization must know which Salesforce record the user is acting upon. Salesforce documentation therefore requires the consultant to select the appropriate record ID when configuring the action. The record ID is the primary identifier for the Salesforce object, and it must be available as part of the visualization. For Contact-based actions, this means mapping the Contact ID so that Tableau Next can invoke the action against the correct Contact record.
The multi-row selection setting in A is not the fundamental record-context requirement for a standard Salesforce action. Likewise, B is misleading. Users certainly require authorization to execute the underlying Salesforce action, but Tableau Next does not require the consultant to create a special Tableau-specific custom permission set merely to map the action.
Architecturally, Tableau Next integrates the analytical and transactional layers by associating visualization data with Salesforce object identifiers. Once a user selects the relevant data element, Tableau Next can pass the corresponding record identity into the configured Salesforce action.
References/Topics: Visualizations and Dashboards - > Add Actions to Visualizations - > Salesforce Actions -
> Record ID Mapping.
NEW QUESTION # 33
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