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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Managing Workspaces & Orgs | 10% | - Asset Deployment
|
| Topic 2: Embedding, Cross-Cloud, & Interoperability | 20% | - Developer Tools and APIs
|
| Topic 3: Agentic Experiences | 25% | - Analytics Agent
|
| Topic 4: Basic Setup & Admin | 10% | - Agentic Analytics
|
| Topic 5: Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Topic 6: Data Setup | 20% | - Data Architecture
|
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NEW QUESTION # 17
Universal Containers wants to ensure its users are able to view, explore, and follow metrics. What is the minimum license level that grants this ability?
Answer: A
Explanation:
The minimum general Tableau Next persona that can view, explore, and follow metrics is the Tableau Unmetered Consumer level represented by B.
Salesforce documents that Consumer users can access the Tableau Next home experience, use Tableau Agent, view workspaces, dashboards, and visualizations, and view, explore, and follow metrics. Salesforce's metric- specific documentation likewise identifies Tableau Unmetered Consumer and equivalent Consumer/Self- Service Consumer permission sets as sufficient to follow metrics.
A Self-Service Analyst can also perform these actions, but that persona includes significantly broader capabilities and therefore is not the minimum required level. Analysts can work with Tableau Next Studio and, depending on the permission set, create or edit analytical content.
An Included App license is narrower. Included App/Limited Consumer personas are designed primarily to interact with prepackaged Tableau Next Apps for Salesforce rather than provide general Tableau Next home and metric exploration capabilities.
The exam principle is to select the least-privileged persona that fully satisfies the requirement, rather than assigning authoring permissions merely because they also include consumption capabilities.
References/Topics: Basic Setup and Admin - > Tableau Next Licenses and Permission Sets - > Consumer - > Metric Exploration and Following.
NEW QUESTION # 18
What is a logical view within a semantic data model?
Answer: B
Explanation:
A Logical View is a semantic data object that combines underlying objects through explicitly configured joins or unions and presents the resulting structure as a single analytical object. Of the choices provided, A correctly captures this concept: the view contains participating objects whose join structure and relationship characteristics must be defined.
Salesforce's current glossary defines a Logical View as a data object that combines multiple tables using special joins and then allows that enriched dataset to be queried as one object. It can subsequently participate in calculated fields, metrics, semantic relationships, and other definitions.
Proper cardinality is important because Tableau Semantics must know whether objects relate one-to-one, one- to-many, many-to-one, or many-to-many to prevent duplicate aggregation or missing results. Salesforce provides explicit cardinality configuration for semantic relationships.
Option B confuses a Logical View with ordinary semantic relationships inherited or defined among data objects. Option C describes neither the structure nor purpose of Logical Views.
The critical exam distinction is relationships preserve separate objects, while a Logical View combines objects into a single logical analytical structure.
References/Topics: Data Setup - > Tableau Semantics - > Logical Views - > Joins - > Cardinality.
NEW QUESTION # 19
Cloud Kicks (CK) has created Tableau Next dashboards and visualizations in a sandbox. These assets rely on new semantic models also developed in the same sandbox. CK's Tableau Next Consultant plans to use a data kit to deploy all assets to the production org. During the data kit creation process, they added the dashboards and visualizations. Which step must the consultant perform to ensure the deployment succeeds?
Answer: A
Explanation:
When Tableau Next assets and their semantic-model dependencies are deployed through a Data Kit, the consultant must explicitly review and correct the publishing sequence. Salesforce documents a minimum dependency sequence of Semantic Models - > Workspaces - > Visualizations - > Dashboards. This ordering is mandatory because visualizations depend on both semantic models and workspaces, while dashboards depend on their visualizations. Salesforce specifically warns that deployment can fail if the publishing sequence isn't reviewed and updated appropriately.
Selecting DevOps is part of creating the deployment Data Kit, but it does not automatically resolve every dependency sequence, making B insufficient. Salesforce notes that the default sequence can be based on asset creation dates and therefore might not match the required dependency order. A is also incorrect because semantic models and Tableau Next assets can be included in a Data Kit deployment to a production home org; deploying the semantic model separately through a change set is not the required approach.
References/Topics: Managing Workspaces and Orgs - > Data Kits - > DevOps Deployment - > Publishing Sequence - > Dependency Management.
NEW QUESTION # 20
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: B
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 # 21
A Tableau Next Consultant is advising a customer on when to use Tableau Agent versus building a traditional Tableau Next dashboard. Which scenario is the best fit for Tableau Agent?
Answer: C
Explanation:
Tableau Agent is optimized for conversational, exploratory analytics in which a business user asks natural- language questions and receives grounded answers and visualizations. A request such as, "What are my top accounts by Annual Contract Value this quarter?" maps directly to Tableau Agent's supported descriptive- analysis capabilities. Salesforce explicitly lists Top-N questions, aggregations, dimensional breakdowns, comparisons, and other business-oriented analytical questions among the supported conversational patterns.
A fixed monthly-close report for a board is better represented by a governed dashboard or reporting asset because its structure, presentation, and recurring content are predetermined. Likewise, Tableau Agent is not positioned as a general-purpose data-science workflow development environment.
The architectural distinction is important for the exam: dashboards provide curated, repeatable analytical experiences, whereas Tableau Agent adds an interactive conversational layer over semantic models. It translates the user's business question into semantic analytical operations and returns contextual text and visual output.
References/Topics: Agentic Experiences - > Analyze and Share Data in Tableau Next - > About Conversational Analytics - > Supported Questions and Surfaces.
NEW QUESTION # 22
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