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| Section | Weight | Objectives |
|---|---|---|
| Agentic Experiences | 25% | - Generative AI
|
| Basic Setup & Admin | 10% | - User Access
|
| Managing Workspaces & Orgs | 10% | - Personal Org
|
| Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Data Setup | 20% | - Data 360
|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Salesforce Analytics Integration
|
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NEW QUESTION # 51
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: B
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 # 52
Universal Containers is concerned about Personally Identifiable Information (PII) being exposed when using Data Connection and Analytics Creation capabilities to create calculated fields. How does Data Connection and Analytics Creation ensure data security when processing requests through the large language model (LLM)?
Answer: A
Explanation:
The correct security mechanism is the Einstein Trust Layer's PII masking capability. Salesforce guidance for AI-assisted calculated-field creation states that the agent may use information from the semantic model, including its schema and metadata, and that personally identifiable information is masked by the Einstein Trust Layer before information is sent to the LLM.
This allows Tableau Next's generative functionality to receive the semantic context required to construct useful calculated fields while applying Salesforce's enterprise AI security controls.
Option A describes a whole-model encryption/decryption workflow that is not the documented Tableau Next processing model. Option C is also incorrect because the system does not simply prohibit every field that could potentially contain PII. Instead, the Trust Layer applies masking and other controls to protect sensitive information while retaining useful analytical context.
More broadly, Salesforce states that Tableau Agent and Agentforce inherit the Einstein Trust Layer's security, governance, and trust mechanisms, including protections designed to prevent customer data from being retained by external LLMs for model training.
References/Topics: Agentic Experiences - > Einstein Trust Layer - > PII Masking - > Generative AI Calculated Fields.
NEW QUESTION # 53
A Tableau Next Consultant is asked to configure Slack integration for proactive alerts. Which setup step is required?
Answer: B
Explanation:
The administrator must enable Collaborate with Slack and Tableau Next, making A correct. Salesforce's documented setup requires connecting the Salesforce org to Slack and then navigating to Tableau Next Administration settings to confirm that Collaborate with Slack and Tableau Next is enabled.
For Inspector Proactive Data Alerts specifically, Salesforce states that Slack must first be enabled for Tableau Next. Users can then receive Inspector alerts through Slack after the Agentforce app and associated connection are configured.
Option B is not the documented prerequisite. Tableau Next relies on appropriate Tableau Next permissions plus Salesforce/Slack identity and connection configuration; assigning a generic "Slack User" permission set is not the required answer.
Option C is also inaccurate as written. A properly configured Analytics and Visualization agent must contain the relevant Data Analysis and Data Alert Management capabilities, but administrators do not necessarily need to create an entirely new agent solely because Slack is being enabled; an existing qualifying agent can be configured and activated.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next with Slack - > Inspector Alerts - > Collaboration Settings - > Agentforce App.
NEW QUESTION # 54
A Tableau Next Consultant wants to implement a Tableau Agent within Tableau Next to provide conversational insights and automated chart summaries for its sales operations managers. The deployment strategy requires using a preconfigured platform framework to accelerate the setup. How should the consultant deploy this specific conversational analytics capability?
Answer: C
NEW QUESTION # 55
A Tableau Next Consultant wants to programmatically update the color schema of a Tableau Next visualization. Which tool is most appropriate to meet this requirement?
Answer: C
Explanation:
The Tableau Next Connect REST API is the appropriate interface when a developer or consultant needs to programmatically configure or update Tableau Next visualization assets. Salesforce documents that the API supports creating and updating visualizations and workspaces and exposes dedicated visualization resources through the /tableau/visualizations endpoints.
Because visualization appearance and configuration are properties of the visualization asset, a programmatic modification to its color configuration belongs to the Tableau Next REST API development surface.
The Semantic Layer DX VS Code Extension is focused on semantic-layer development and metadata associated with semantic models; it is not the primary API for editing visualization presentation properties.
Salesforce CLI is an extensible deployment and administration tool, but it is not the dedicated Tableau Next runtime interface for modifying visualization configuration.
Salesforce's Tableau Next development documentation explicitly positions the Connect REST APIs as the developer interface for configuring and managing Tableau Next visualizations and workspaces. The API therefore provides the correct abstraction when visualization changes must be automated, integrated into an application, or performed through code.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next Development - > Connect REST API - > Visualization Resources.
NEW QUESTION # 56
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