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| Section | Weight | Objectives |
|---|---|---|
| Data Setup | 20% | - Data Architecture
|
| Agentic Experiences | 25% | - Generative AI
|
| Managing Workspaces & Orgs | 10% | - Personal Org
|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Developer Tools and APIs
|
| Basic Setup & Admin | 10% | - Agentic Analytics
|
| Visualizations & Dashboards | 15% | - Dashboard Actions
|
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NEW QUESTION # 73
Universal Containers wants to allow sales reps to ask natural language questions about their pipeline directly from Salesforce mobile. Which configuration is required?
Answer: C
Explanation:
The correct requirement is to enable the conversational analytics capability represented by Agentforce for Analytics, now called Tableau Agent. Salesforce explicitly lists the Salesforce Mobile app as a supported surface for Tableau Agent with the Data Analysis subagent. Users can ask natural-language analytical questions within Salesforce and receive grounded answers and visualizations based on their semantic models.
The terminology in option A is older but still maps directly to the current capability. Salesforce states that, beginning in July 2026, Agentforce for Analytics in Tableau Next is called Tableau Agent, while Concierge:
Analytics Q & A became the conversational analytics capability enabled by Data Analysis.
No custom Lightning component is required merely to expose this supported conversational experience on Salesforce mobile. Likewise, deploying traditional dashboards to mobile would enable dashboard consumption but would not itself provide the requested natural-language Q & A experience.
References/Topics: Agentic Experiences - > Tableau Agent - > Data Analysis - > Salesforce Mobile - > Conversational Analytics.
NEW QUESTION # 74
Cloud Kicks stores historical customer transaction data inside Snowflake. The marketing team wants to track campaign performance in Tableau Next. However, IT compliance strictly prohibits creating duplicate copies of this dataset due to storage costs and security synchronization risks. Which architectural feature should a Tableau Next Consultant implement to meet these requirements?
Answer: C
Explanation:
Zero Copy Data Federation is the correct architectural approach because it allows Tableau Next and Data 360 to work with Snowflake-hosted data without creating a separate duplicated dataset. The Snowflake tables remain in the source platform while the federation layer exposes them for governed analytical use. This directly addresses both storage-cost concerns and the compliance risk associated with maintaining synchronized copies.
Option B would move the data into Salesforce custom objects through an integration flow, which creates another persisted copy and increases synchronization and governance overhead. Option C also creates replicated data through scheduled batch processing and therefore violates the stated requirement to avoid duplication. Zero-copy access keeps the source system authoritative while making the dataset available for semantic modeling and Tableau Next analysis.
The important architecture pattern is federation rather than extraction: connect Snowflake, expose the required federated data objects, apply the necessary governance, and then build the Tableau Next semantic layer over those objects. This minimizes data movement while preserving analytical accessibility.
References/Topics: Data Setup - > Data 360 - > Snowflake - > Zero Copy Data Federation - > Tableau Next.
NEW QUESTION # 75
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: B
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 # 76
Which statement accurately describes a parameter within a Tableau Next semantic model?
Answer: C
Explanation:
A parameter is a user-controllable variable that can influence calculations, filtering, reference lines, and other interactive analytical behavior. Salesforce documents parameters as a mechanism for modeling scenarios and allowing dashboard users to provide inputs that affect analytical results. Parameters can be created for different data types and then referenced by calculated fields or dashboard controls.
For example, an organization could define a parameter named Target Discount and allow a user to enter 15%.
A calculated field could then compare actual discount values with the parameter and dynamically change the resulting visualization. Tableau Next also supports parameter widgets that accept manually entered values or derive dynamic values from dashboard queries.
Option B incorrectly describes semantic-model relationship configuration. Relationships between DMOs are defined through relationship metadata and cardinality rather than parameters. Option C confuses parameters with governance and authorization controls.
The certification distinction is: parameters provide variable analytical input; calculated fields consume that input; semantic relationships define object connectivity; Data 360 governance controls security.
References/Topics: Data Setup - > Semantic Models - > Parameters - > Calculated Fields - > Interactive Scenario Modeling.
NEW QUESTION # 77
A Tableau Next Consultant is asked to configure caching for a high-volume data source. Which refresh method ensures deleted records are reflected?
Answer: B
Explanation:
Full Refresh is required when the accelerated Tableau Next cache must reflect records that were deleted in the external source. Salesforce documentation distinguishes the two acceleration modes explicitly. An Incremental Refresh adds or updates records that changed after the previous refresh, but it does not update deleted records.
By contrast, a Full Refresh removes all previously cached data during each refresh cycle and replaces it with a newly retrieved copy of the current source dataset. If a source record has been deleted, it no longer exists in the replacement dataset and consequently disappears from Tableau Next.
Incremental refresh can operate as frequently as every 15 minutes, making it attractive for high-frequency changes, but that frequency does not alter its deletion limitation. If deletion synchronization is a requirement, the architecture must account for periodic or continuous full-refresh behavior according to supported refresh intervals.
"Snapshot refresh" is not one of the documented Tableau Next Acceleration refresh methods for this use case.
This is the same architectural principle tested earlier: Incremental = added/changed data; Full = complete cache replacement, including removal of deleted source records.
References/Topics: Data Setup - > Acceleration for Data Connections - > Cache Refresh Method - > Full versus Incremental Refresh.
NEW QUESTION # 78
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