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| Section | Weight | Objectives |
|---|---|---|
| Plan and Prepare Data Connections | 22% | - Plan for data transformation
|
| Design and Troubleshoot Calculations and Workbooks | 40% | - Optimize workbook performance
|
| Establish Governance and Support Published Content | 16% | - Apply governance strategy
|
| Evaluate Current State | 22% | - Map current state of analytics to future state
|
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NEW QUESTION # 67
A Tableau Next Consultant is configuring a Salesforce action in a Tableau Next table visualization that displays Contact records. The goal is to give sales reps the ability to trigger a screen flow that adds selected Contacts to a Campaign. What is a required configuration step for the action to work correctly?
Answer: B
Explanation:
A Salesforce action executed from a Tableau Next visualization must know which Salesforce record the user is acting upon. Salesforce documentation therefore requires the consultant to select the appropriate record ID when configuring the action. The record ID is the primary identifier for the Salesforce object, and it must be available as part of the visualization. For Contact-based actions, this means mapping the Contact ID so that Tableau Next can invoke the action against the correct Contact record.
The multi-row selection setting in A is not the fundamental record-context requirement for a standard Salesforce action. Likewise, B is misleading. Users certainly require authorization to execute the underlying Salesforce action, but Tableau Next does not require the consultant to create a special Tableau-specific custom permission set merely to map the action.
Architecturally, Tableau Next integrates the analytical and transactional layers by associating visualization data with Salesforce object identifiers. Once a user selects the relevant data element, Tableau Next can pass the corresponding record identity into the configured Salesforce action.
References/Topics: Visualizations and Dashboards - > Add Actions to Visualizations - > Salesforce Actions -
> Record ID Mapping.
NEW QUESTION # 68
Cloud Kicks (CK) wants to scale out its semantic data tier but has limited Tableau Next Consultant resources.
CK wants to identify tasks where Tableau Agent's generative AI capabilities can directly accelerate the delivery of Tableau Next components. Which task can Tableau Agent directly perform within the semantic data model configuration canvas?
Answer: B
Explanation:
Generative AI capabilities in Tableau Semantics can directly accelerate semantic-model authoring by drafting calculated-field formulas and semantic descriptions, making A the correct choice. Salesforce supports Draft with Einstein, where the consultant describes the calculation in natural language and Einstein generates the calculated-field definition, including formula-related configuration that the author can review and save.
Salesforce also provides AI-generated semantic descriptions. These descriptions supply business context to downstream conversational analytics and help Tableau Agent correctly discover and interpret objects and fields.
Identity resolution and DMO mapping belong to Data 360 data-modeling and identity-management workflows, not the semantic-model generative-authoring capability described in this scenario. Dashboard and visualization construction is also a separate analytics-authoring process rather than the specified operation within the semantic data model configuration canvas.
The exam principle is that Tableau Agent/Semantics AI reduces semantic-authoring friction by translating natural-language analytical intent into semantic definitions, relationships, descriptions, and calculations.
References/Topics: Agentic Experiences - > generative AI for Tableau Next components; Create Semantic Models - > AI-assisted calculated fields and descriptions.
NEW QUESTION # 69
A Tableau Next Consultant shares a metric in Slack that contains sensitive data governed by Data 360 policies. A user who does not have a Tableau Next license views the shared message in Slack and can see the metric image. The consultant is concerned there's a problem with the data security setup. Which statement correctly describes this behavior?
Answer: C
Explanation:
For a standard Tableau Next Slack message preview, Salesforce explicitly warns that anyone who can see the Slack message can see its preview, including filters applied when it was shared. Consequently, users should verify that the preview does not expose inappropriate sensitive information before posting it into a channel or conversation.
Tableau Next's Slack integration generates previews according to the sender's permission access and Tableau Next governance context. Once that snapshot-style preview is shared, visibility of the message governs who can see that static representation.
Therefore, C correctly describes the behavior. There is no indication that Data 360 security has malfunctioned.
Option A is wrong because recipients do not automatically obtain unrestricted interactive access to the underlying Tableau Next asset. Option B incorrectly assumes that each static Slack preview is dynamically authorization-checked as though the recipient were opening Tableau Next.
A critical distinction is that Slack Canvas cards behave differently: Canvas previews can refresh using each viewer's Tableau Next access, and unauthorized users cannot see the live underlying content.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next in Slack - > Shared Previews - > Governance.
NEW QUESTION # 70
A data analyst at Cloud Kicks has been tasked with creating and sharing Tableau Next assets, including workspaces and dashboards. The user also needs to manage a Personal Org. They have been assigned a Tableau Next Creator license. Which permission set should a Tableau Next Consultant assign to this user to fulfill these requirements?
Answer: C
Explanation:
Salesforce guidance states that a Tableau Next Self-Service Analyst requires a Tableau Next Creator license and provides access to Tableau Next Studio, Tableau Agent, Personal Org ownership, analytical assets, and self-service creation/editing functionality within the Personal Org. Personal Org owners can create workspaces and dashboards and can share their workspace with other analysts under the Personal Org collaboration model.
Because this question expressly includes management of a Personal Org and is framed around a self-service analyst persona, C remains the correct exam-bank answer.
References/Topics: Managing Workspaces and Orgs - > Personal Org - > Tableau Next Creator - > Self- Service Analyst Permissions.
NEW QUESTION # 71
Cloud Kicks has built a highly curated semantic data model (SDM) in Tableau Next containing all of its business rules, metric definitions, and generative AI field descriptions. However, another team of analysts want to use this exact same business logic to build custom visualizations in Tableau Cloud. What should the Tableau Next Consultant recommend to this team?
Answer: B
Explanation:
The correct approach is to use the Tableau Semantics connector from Tableau Cloud. Salesforce explicitly supports connecting Tableau Desktop and Tableau Cloud directly to semantic models defined in Data 360
/Tableau Semantics. This allows downstream Tableau authors to consume the same governed measures, dimensions, calculations, relationships, metrics, and business definitions that Tableau Next uses.
Option B would undermine the principal benefit of the semantic layer. Reconnecting directly to Data 360 objects and recreating joins would force analysts to reconstruct business logic and could lead to inconsistent calculations or relationships across analytical applications. Option C is also incorrect because Data Kits are Salesforce/Data 360 deployment mechanisms; they are not used to install semantic models into Tableau Cloud as independent Tableau data models.
This interoperability capability is strategically important: Tableau Semantics provides one governed analytical definition layer that can be consumed across Tableau Next, Tableau Cloud, Tableau Desktop, AI experiences, and other supported Salesforce applications. Analysts can therefore create custom Tableau Cloud visualizations without duplicating semantic logic.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Semantics Connector - > Tableau Cloud - > Reusable Semantic Models.
NEW QUESTION # 72
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