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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and Prepare Data Connections | 22% | - Plan for data transformation
|
| Topic 2: Establish Governance and Support Published Content | 16% | - Apply governance strategy
|
| Topic 3: Design and Troubleshoot Calculations and Workbooks | 40% | - Optimize workbook performance
|
| Topic 4: Evaluate Current State | 22% | - Map current state of analytics to future state
|
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NEW QUESTION # 67
Cloud Kicks (CK) uses CRM Analytics (CRMA) for operational embedded reporting within its Agentforce Sales console and Tableau Cloud for historical deep- dive executive dashboards. CK is now evaluating the addition of Tableau Next to its analytics architecture. Which statement accurately describes the distinct positioning benefit of adding Tableau Next to this multi- platform ecosystem?
Answer: B
Explanation:
Tableau Next's distinctive value is its agentic, conversational, and actionable analytics layer, so C is correct.
Salesforce positions Tableau Next as an end-to-end agentic analytics platform combining Tableau analytics, Agentforce AI, and the Data 360 semantic layer. It enables users to ask freeform analytical questions, receive grounded text and visual answers, obtain proactive insights, and initiate actions where work occurs.
The platform is therefore complementary to existing analytical investments. Tableau Cloud can continue supporting sophisticated traditional analytics and executive exploration, while CRM Analytics can continue supporting embedded Salesforce analytical use cases. Tableau Next introduces a governed semantic and agentic layer that makes data conversational and actionable.
Option A is too absolute. Salesforce interoperability capabilities explicitly support connecting Tableau Cloud to Tableau Semantics, illustrating coexistence rather than mandatory replacement. Option B also mischaracterizes Published Data Source integration: Tableau Next can build semantic models directly from supported Tableau Cloud PDS content; its purpose is not merely extraction into DMOs.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next Positioning - > Tableau Agent - > Tableau Cloud and CRM Analytics Coexistence.
NEW QUESTION # 68
A Tableau Next Consultant is shadowing a client's business analyst who is building a new profitability dashboard in Tableau Next. The analyst knows exactly the business logic they need for a complex "Year- over- Year Weighted Margin" metric, but they are new to the platform and keep getting syntax errors when trying to write the formula. How does generative AI in Tableau Next assist the analyst in this scenario?
Answer: A
Explanation:
Tableau Next provides generative AI capabilities that translate a user's natural-language description of a calculation into a calculated-field formula. This directly addresses scenarios where an analyst understands the required business logic but lacks familiarity with Tableau Next formula syntax.
With Draft with Einstein, the user describes the calculation they need in natural language. Einstein can propose the field name, description, data type, aggregation type, and formula. The agentic calculated-field experience also supports conversational refinement, allowing the user to explain requirements and respond to clarification questions before reviewing the proposed field.
A batch transform, as described in A, is a data-preparation mechanism and is unrelated to helping an analyst overcome formula-authoring syntax problems. C is less accurate because the defining generative-AI capability being tested is the transformation of natural-language analytical intent into a proposed formula.
The generated output remains subject to user review before creation, preserving human control over the final semantic definition while substantially reducing formula-authoring friction.
References/Topics: Agentic Experiences - > Generative AI - > Draft with Einstein/Data Pro - > Natural- Language Calculated Fields.
NEW QUESTION # 69
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 # 70
A Tableau Next Consultant has shared a workspace with a group of users and granted them Editor access at the workspace level. However, one of the users reports that they are still unable to edit a dashboard within that workspace. What is the most likely reason for this issue?
Answer: C
Explanation:
Tableau Next applies both asset-sharing permissions and platform permission sets. Granting Editor access through workspace sharing cannot elevate a user's capabilities beyond those granted by the administrator.
Salesforce explicitly states that sharing doesn't override permissions set by the admin and that a user who lacks the permission set required to edit Tableau Next assets cannot edit an asset even when granted Editor access.
Therefore, C is correct.
Workspace-level access is designed to simplify administration. Users and Analytics Groups can be granted Viewer or Editor access to a workspace, with appropriate access applying to contained assets subject to underlying security and permission requirements. Consequently, B is incorrect as a general explanation.
Option A is also incorrect. Workspace owners can share assets subject to their own permissions, but inability of the affected user to edit is not because dashboards universally require a separate owner-assigned Editor permission.
Think of Tableau Next authorization as multiple gates: license - > Tableau Next permission set - > asset sharing - > underlying data access. A more permissive setting at a downstream sharing layer cannot bypass a restrictive upstream administrative permission.
References/Topics: Managing Workspaces and Orgs - > Workspace Sharing - > Editor Access - > Tableau Next Permission Sets - > Permission Inheritance.
NEW QUESTION # 71
A Tableau Next Consultant is advising a retail company that wants to track its monthly sales conversion rate against a fixed benchmark in Tableau Next. The metric is non- cumulative. Which feature should the consultant recommend configuring on the metric?
Answer: C
Explanation:
A threshold is the appropriate configuration because the requirement is to evaluate a non-cumulative metric against a fixed benchmark. Salesforce describes thresholds as contextual reference values that classify a metric into meaningful ranges such as healthy, at risk, or critical. Salesforce specifically notes that thresholds can be used independently of goals and are particularly useful for non-cumulative metrics.
A goal is better suited to measuring progress toward a target, particularly when progress accumulates over a defined time period. For example, a sales-revenue goal can indicate whether the organization is on pace to reach a quarterly target. By contrast, a conversion percentage is normally evaluated as a current rate rather than accumulated toward a total.
Forecasting Insights addresses a different analytical requirement: estimating likely future metric behavior from historical patterns. It does not establish the fixed performance benchmark required here.
For exam purposes, distinguish goal = progress toward target, threshold = contextual/static performance boundary, and forecast = projected future behavior.
References/Topics: Visualizations and Dashboards - > Metrics - > Goals and Thresholds - > Non- Cumulative Metrics.
NEW QUESTION # 72
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