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| Section | Weight | Objectives |
|---|---|---|
| Basic Setup & Admin | 10% | - Access Management
|
| Agentic Experiences | 25% | - Analytics Agent
|
| Data Setup | 20% | - Semantic Models
|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Salesforce Analytics Integration
|
| Visualizations & Dashboards | 15% | - Visualization and Dashboard Design
|
| Managing Workspaces & Orgs | 10% | - Asset Management and Sharing
|
>> Exam Salesforce Analytics-Con-202 Question <<
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NEW QUESTION # 19
A Tableau Next Consultant needs to explicitly define an inner join between two data objects to create a new, single abstract table for their semantic model. Which feature should the consultant use?
Answer: B
Explanation:
A Logical View is the correct feature when the consultant needs to combine multiple data objects through an explicitly defined join and expose the resulting structure as a single reusable semantic object. Salesforce defines a logical view as a data object that combines multiple underlying objects using joins or unions rather than standard semantic relationships. The resulting logical view can then participate in relationships, calculated fields, metrics, and other semantic definitions as though it were an ordinary data object.
This distinction is fundamental. A standard relationship keeps the participating objects logically separate and describes how Tableau Semantics should traverse between them during query generation. It does not materialize their joined structure into one abstract semantic object. A Calculated Insight is used for more advanced Data 360 calculations and aggregations and does not represent the semantic-model join construct required here.
When configuring a Logical View, the consultant defines the participating objects, join criteria, join type- including an inner join when required-and appropriate cardinality. Correct join and cardinality configuration prevents duplicate or missing analytical results.
References/Topics: Data Setup - > Tableau Semantics - > Logical Views - > Joins - > Cardinality.
NEW QUESTION # 20
A Tableau Next Consultant wants to enable conversational analytics for marketing data stored in Snowflake.
What is required?
Answer: B
Explanation:
Tableau Agent's conversational analytics depends on an AI-ready Tableau semantic model, making A correct.
Salesforce positions Tableau Semantics as the governed business layer between connected Data 360 sources and analytical or AI consumption experiences. Semantic models define standardized measures, dimensions, relationships, calculations, metrics, terminology, and business context that Tableau Agent uses to interpret natural-language questions.
For Snowflake data, the consultant establishes an appropriate Data 360 connection-including supported zero- copy federation where appropriate-and exposes the required Snowflake data through Data 360. The consultant then builds and prepares a semantic model containing the marketing concepts that Tableau Agent must analyze. Salesforce's Tableau Agent implementation guidance explicitly requires determining the required data, connecting it through Data 360, and creating suitable semantic foundations before configuring conversational analytics.
CSV export is unnecessary and creates an avoidable duplicate dataset. Building dashboards directly in Snowflake also does not establish Tableau Agent's governed semantic context.
The architecture is therefore: Snowflake - > Data 360 connectivity - > Tableau Semantic Model - > Tableau Agent - > Conversational Analytics.
References/Topics: Data Setup - > Snowflake Integration - > Data 360 - > Tableau Semantics - > AI-Ready Semantic Models.
NEW QUESTION # 21
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: C
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 # 22
What is a logical view within a semantic data model?
Answer: C
Explanation:
A Logical View is a semantic data object that combines underlying objects through explicitly configured joins or unions and presents the resulting structure as a single analytical object. Of the choices provided, A correctly captures this concept: the view contains participating objects whose join structure and relationship characteristics must be defined.
Salesforce's current glossary defines a Logical View as a data object that combines multiple tables using special joins and then allows that enriched dataset to be queried as one object. It can subsequently participate in calculated fields, metrics, semantic relationships, and other definitions.
Proper cardinality is important because Tableau Semantics must know whether objects relate one-to-one, one- to-many, many-to-one, or many-to-many to prevent duplicate aggregation or missing results. Salesforce provides explicit cardinality configuration for semantic relationships.
Option B confuses a Logical View with ordinary semantic relationships inherited or defined among data objects. Option C describes neither the structure nor purpose of Logical Views.
The critical exam distinction is relationships preserve separate objects, while a Logical View combines objects into a single logical analytical structure.
References/Topics: Data Setup - > Tableau Semantics - > Logical Views - > Joins - > Cardinality.
NEW QUESTION # 23
Cloud Kicks wants to track and analyze user dashboard interactions with its Tableau Next assets for governance and adoption monitoring. Which capability should a Tableau Next Consultant activate to begin collecting user interaction data?
Answer: C
Explanation:
User Interaction Logging is the capability used to begin collecting interaction data for governance and adoption analysis. In this scenario, Cloud Kicks needs visibility into how users interact with Tableau Next dashboard assets so administrators can evaluate usage patterns, adoption, and engagement. Enabling interaction logging creates the foundation for capturing those user events and making them available for downstream monitoring and analysis.
Tableau Next Auditing is associated with broader administrative audit and governance use cases, while Session Tracing is oriented toward tracing agent sessions and AI behavior. Neither is the specific capability identified here for initiating dashboard interaction collection. The requirement is centered on user activity against Tableau Next assets rather than agent reasoning or session diagnostics.
A consultant should distinguish telemetry collection from downstream analysis. First, interaction events must be captured through User Interaction Logging; those events can then be analyzed to understand which assets are used, how users engage with dashboards, and where adoption or governance attention is required. This supports operational oversight without changing the analytical content itself.
References/Topics: Basic Setup and Admin - > Tableau Next User Interaction Logging - > Governance and Adoption Monitoring.
NEW QUESTION # 24
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