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| Section | Weight | Objectives |
|---|---|---|
| Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Basic Setup & Admin | 10% | - Access Management
|
| Managing Workspaces & Orgs | 10% | - Asset Management and Sharing
|
| Agentic Experiences | 25% | - Generative AI
|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Tableau Next Apps and Marketplace
|
| Data Setup | 20% | - Data 360
|
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NEW QUESTION # 18
A financial services firm requires its Analytics Agent to consistently provide concise responses and format all currency outputs in Great British Pounds (GBP). Where should a Tableau Next Consultant configure these global formatting and output style rules?
Answer: A
Explanation:
Business Preferences are the semantic-model mechanism for supplying organization-specific instructions and contextual guidance to Tableau Agent. They can define how the analytics agent should interpret business concepts, terminology, and preferred response conventions. Salesforce recommends keeping each Business Preference short, focused, and high-value because these instructions are added to the agent's prompt.
Accordingly, preferences such as "Use GBP when presenting monetary values" or "Keep responses concise" belong in Business Preferences rather than individual field descriptions. A field description explains what a particular semantic field means; it is not the proper location for broadly applicable output behavior. The Einstein Trust Layer addresses AI trust, security, privacy, and governance controls rather than organization- specific response formatting.
References/Topics: Agentic Experiences - > Business Preferences - > Organizational Terminology - > Response Guidance - > Semantic Model Context.
NEW QUESTION # 19
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 # 20
A Tableau Next Consultant is asked to configure row-level security (RLS) for sensitive HR data. Where should this be defined?
Answer: B
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 # 21
A team at Universal Containers collaborates frequently in Slack. The goal is to share a Tableau Next metric within a Slack canvas, ensuring it appears as a rich preview where the data regularly refreshes for each team member. All team members have appropriately assigned licenses. Which procedure should a Tableau Next Consultant instruct a user to follow to achieve this?
Answer: B
Explanation:
For a live Tableau Next preview inside a Slack canvas, Salesforce instructs users to paste the Tableau Next asset URL into the canvas and select Card from the Paste As menu. The resulting card can display a metric, dashboard, or visualization and regularly refresh its underlying data.
This behavior differs materially from sharing a static Tableau Next preview in an ordinary Slack channel or direct message. In a Canvas, Salesforce retrieves the data from each viewer's perspective. Consequently, each person must have appropriate Tableau Next access to the underlying asset and data. Unauthorized users receive an access message instead of seeing protected data. This preserves individual data governance while still providing a rich collaborative experience.
Option A does not describe the documented Slack Canvas workflow. Option C produces a static image and therefore fails the requirement for regularly refreshed information.
The exam distinction is important: standard Slack message preview = snapshot governed by sharing behavior; Slack Canvas Card = live, refreshable preview evaluated against each viewer's access.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next in Slack - > Slack Canvas - > Paste As Card - > Viewer-Based Data Access.
NEW QUESTION # 22
A Tableau Next Consultant needs to migrate dashboards from a sandbox org to production. Which deployment mechanism should be used?
Answer: C
Explanation:
Data Kits are a native supported deployment mechanism for moving Tableau Next assets from a sandbox to a production Data 360 home org. Salesforce explicitly states that Tableau Next workspaces, visualizations, and dashboards can be deployed through Data Kits, and that Data 360 semantic models on which those analytical assets depend must also use Data Kits for deployment to target home orgs.
CSV export/import is a data-transfer technique, not a Tableau Next metadata lifecycle-management mechanism. It cannot preserve dashboard structure, visualization definitions, semantic-model dependencies, workspace metadata, or the relationships between these assets. Manual recreation would be operationally inefficient, prone to configuration drift, and unnecessary when supported deployment tooling exists.
A technically complete implementation must also account for dependency sequencing. When a Data Kit contains the semantic model and downstream Tableau Next content, Salesforce requires the publishing order to be at least Semantic Models - > Workspaces - > Visualizations - > Dashboards.
References/Topics: Managing Workspaces and Orgs - > Sandbox Development - > Data Kits - > Production Deployment - > Asset Dependencies.
NEW QUESTION # 23
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