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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Establish Governance and Support Published Content | 16% | - Apply governance strategy
|
| Topic 2: Design and Troubleshoot Calculations and Workbooks | 40% | - Optimize workbook performance
|
| Topic 3: Plan and Prepare Data Connections | 22% | - Plan for data transformation
|
| Topic 4: Evaluate Current State | 22% | - Evaluate current data structures
|
>> Analytics-Con-202 Exam Passing Score <<
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NEW QUESTION # 30
A Tableau Next Consultant is asked to configure workspace access for sensitive dashboards. Which General Access setting ensures no one can see dashboards by default?
Answer: C
Explanation:
Restricted is the correct General Access state. Salesforce documents that newly created Tableau Next assets are restricted by default. When General Access remains restricted, only individual users or Analytics Groups that have been explicitly granted access can open the asset.
For sensitive dashboards, this provides the correct baseline because access is opt-in rather than org-wide. The owner can then grant specific users or groups Viewer access and, where supported at the workspace level, Editor access.
Salesforce also makes an important distinction between Tableau Next asset access and underlying data access.
Even if a dashboard is shared with a user, that action does not automatically grant permission to the DLOs, DMOs, or data spaces on which the dashboard depends. Data 360 governance still applies separately.
"Public" and "Shared" are not the documented General Access states that produce the required private-by- default behavior. Current Tableau Next access management uses Restricted as the state in which only explicitly shared users or groups can access an asset.
For sensitive content, the architecture should therefore use Restricted asset access + explicit user/group sharing + Data 360 governance.
References/Topics: Managing Workspaces and Orgs - > General Access - > Restricted - > Asset Sharing - > Data Governance.
NEW QUESTION # 31
A Tableau Next Consultant needs to migrate Tableau Next assets and underlying Data 360 semantic models from a sandbox to a production org. Which deployment strategy should the consultant use to deploy all assets together in a single step?
Answer: B
Explanation:
A Data Kit is the correct deployment mechanism when Tableau Next assets and their dependent Data 360 semantic models must be moved together. Salesforce explicitly documents that Tableau Next workspaces, visualizations, and dashboards can be packaged in a Data Kit and that Data 360 semantic models-the primary data source for Tableau Next assets-must be deployed to target home orgs using Data Kits.
The consultant should create a DevOps Data Kit, add the semantic models and Tableau Next assets, and then carefully validate the publishing sequence. Salesforce requires the dependency sequence to be at least:
Semantic Models - > Workspaces - > Visualizations - > Dashboards.
This ordering exists because visualizations depend on both semantic models and workspaces, while dashboards depend on visualizations.
A Change Set can deploy Tableau Next metadata in certain scenarios, but it does not provide the same unified deployment path for the Data 360 semantic-model dependencies described here. Salesforce CLI similarly is not the best answer when the requirement is explicitly to package all these assets together.
References/Topics: Managing Workspaces and Orgs - > Deploy Tableau Next Assets - > DevOps Data Kits -
> Publishing Sequence and Dependencies.
NEW QUESTION # 32
Universal Containers connected an external Model Context Protocol (MCP)- compliant AI client to the Tableau Next MCP server so analysts can query their data from that client. During rollout, an analyst asks the Tableau Next Consultant how data access is determined when they query through the external client instead of signing in to Tableau Next directly. Which statement best describes how the integration governs what each analyst can access?
Answer: B
Explanation:
Tableau Next MCP sessions operate using the OAuth-authenticated identity of the individual user, so B is correct. The external MCP client does not become the authoritative security boundary. Instead, Tableau Next continues to enforce Salesforce/Tableau permissions and governance while exposing analytical capabilities to the external AI environment.
Salesforce's Tableau Next MCP documentation explicitly states that MCP sessions use OAuth-authenticated users and that permissions and restrictions associated with the user's profile apply to the MCP session.
Tableau user permissions, semantic-model definitions, and Trust Layer protections therefore remain effective when the user accesses Tableau Next through an external MCP-compatible client.
Salesforce's broader hosted-MCP architecture follows the same principle: tools enforce per-user authentication and standard Salesforce security controls rather than granting universal access based on connector configuration.
This design preserves governance across interoperability boundaries: Tableau Next remains the governed analytical source, while the external client functions as another interaction surface.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Integrate Analytics Across Platforms -
> Tableau Next MCP Server - > Permissions and Governance.
NEW QUESTION # 33
A Tableau Next Consultant needs to migrate a newly developed Tableau Next semantic model and its associated dashboards from a sandbox to the production environment. The two environments are part of the same Salesforce organization hierarchy. Which deployment method should the consultant use to natively move these assets?
Answer: C
NEW QUESTION # 34
A Tableau Next Consultant with a Creator- level Tableau Next permission set is working on an analytics project that requires combining a production data source with an external data source. The consultant wants to avoid setting up governance on the second data source. Which approach should the consultant take to work on this project and share the results with the stakeholder, who has a Self- Service Analyst- level permission set?
Answer: A
Explanation:
A Personal Org is specifically designed for self-service analysis where an analyst needs to combine governed corporate information with personal or specialized data without introducing that experimental dataset into the managed production governance environment.
Salesforce states that Personal Org enables analysts to combine production data with local or specialized datasets, create semantic models and visualizations, and iterate independently without affecting governed production content. Production assets can also be reused inside Personal Org while their existing production governance remains intact.
Once the analysis is ready, the Personal Org owner can share the relevant workspace with another eligible analyst and grant Viewer or Editor access. Salesforce explicitly documents sharing Personal Org workspaces with Tableau Next Analyst users.
Option B does not provide the isolated self-service environment intended for ungoverned analytical experimentation. Option C unnecessarily moves the analytical workflow into an external MCP client and does not represent the native Tableau Next solution for this use case.
References/Topics: Managing Workspaces and Orgs - > Personal Org - > Combine Governed and Personal Data - > Workspace Sharing.
NEW QUESTION # 35
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