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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Topic 2: Embedding, Cross-Cloud, & Interoperability | 20% | - Salesforce Analytics Integration
|
| Topic 3: Agentic Experiences | 25% | - Agentic Readiness
|
| Topic 4: Data Setup | 20% | - Semantic Models
|
| Topic 5: Managing Workspaces & Orgs | 10% | - Personal Org
|
| Topic 6: Basic Setup & Admin | 10% | - User Access
|
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NEW QUESTION # 28
A mature Tableau customer wants to use the Analytics Agent in Tableau Next. However, they have heavily invested in complex data models and calculations within Tableau Cloud Published Data Sources (PDSs) and refuse to rebuild this logic from scratch in Data 360. How should a Tableau Next Consultant meet this requirement using native interoperability?
Answer: C
Explanation:
Tableau Next provides native interoperability with Tableau Cloud Published Data Sources (PDSs). Salesforce allows a consultant to create a Data 360 semantic model by connecting directly to an existing PDS after establishing the required trust between the Salesforce org and Tableau Cloud site.
The PDS remains the external data definition and query source. Tableau Next inherits fields such as their names and data types, and the semantic model can then be enriched with calculated fields, metrics, descriptions, and business context. Critically, Salesforce states that this approach allows organizations to use existing Tableau content without data or metadata migration.
That precisely addresses the customer's concern about preserving substantial prior investment in Tableau Cloud modeling and calculations.
Options A and B introduce mechanisms that are not the native Tableau Next interoperability pattern documented for PDS reuse. There is no requirement to translate the PDS into Snowflake SQL or convert it into a CRM Analytics recipe.
This architecture enables Tableau Next to extend rather than replace mature Tableau investments, while exposing existing governed analytical logic to Tableau Agent.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Cloud PDS - > Tableau Semantics - > Create Semantic Model from Published Data Source.
NEW QUESTION # 29
Cloud Kicks wants to track and analyze user dashboard interactions with its Tableau Next assets for governance and adoption monitoring. Which capability should a Tableau Next Consultant activate to begin collecting user interaction data?
Answer: B
Explanation:
User Interaction Logging is the capability used to begin collecting interaction data for governance and adoption analysis. In this scenario, Cloud Kicks needs visibility into how users interact with Tableau Next dashboard assets so administrators can evaluate usage patterns, adoption, and engagement. Enabling interaction logging creates the foundation for capturing those user events and making them available for downstream monitoring and analysis.
Tableau Next Auditing is associated with broader administrative audit and governance use cases, while Session Tracing is oriented toward tracing agent sessions and AI behavior. Neither is the specific capability identified here for initiating dashboard interaction collection. The requirement is centered on user activity against Tableau Next assets rather than agent reasoning or session diagnostics.
A consultant should distinguish telemetry collection from downstream analysis. First, interaction events must be captured through User Interaction Logging; those events can then be analyzed to understand which assets are used, how users engage with dashboards, and where adoption or governance attention is required. This supports operational oversight without changing the analytical content itself.
References/Topics: Basic Setup and Admin - > Tableau Next User Interaction Logging - > Governance and Adoption Monitoring.
NEW QUESTION # 30
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 # 31
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: C
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 # 32
During agent testing, a Tableau Next Consultant asks, "Who are the top-performing AEs?" and the Tableau Agent returns results based on opportunity count, when the business definition of "top-performing" is based on annual contract value (ACV). Which configuration change best resolves this issue?
Answer: C
Explanation:
This is a textbook use case for Business Preferences. Salesforce defines Business Preferences as business- specific instructions stored within the semantic model that tell Analytics Q & A how to interpret an organization's terminology, defaults, jargon, and business logic.
The expression "top-performing" is ambiguous in ordinary language. The organization has explicitly defined it to mean performance ranked by Annual Contract Value. A Business Preference such as "When users ask about top-performing AEs, use ACV to determine performance" supplies precisely that missing business context.
Renaming ACV to Performance would reduce semantic clarity and distort the actual meaning of the field.
ACV should retain its authoritative business name.
A Verified Question can help calibrate frequently asked questions and improve responses to semantically similar queries, but the underlying issue here is a reusable business-language interpretation rule, not merely one incorrect Q & A example. Business Preferences are therefore the more appropriate semantic mechanism.
Salesforce also recommends keeping Business Preferences concise and using them for contextual interpretation rather than structured calculations that belong in calculated fields or metrics.
References/Topics: Agentic Experiences - > Business Preferences - > Business Terminology - > Analytics Q
& A Accuracy.
NEW QUESTION # 33
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