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| Section | Weight | Objectives |
|---|
| Topic 1: Visualizations & Dashboards | 15% | - Visualization and Dashboard Design
- 1. Apply visualization and dashboarding best practices to design user-friendly Tableau Next assets
- Dashboard Actions
- 1. Explain how to configure actions within Tableau Next
|
| Topic 2: Basic Setup & Admin | 10% | - Tableau Next Activation and Management
- 1. Explain how to activate and manage Tableau Next features
- Agentic Analytics
- 1. Describe how to activate Agentic Analytics for users
- Access Management
- 1. Identify and apply appropriate access to enable users
|
| Topic 3: Embedding, Cross-Cloud, & Interoperability | 20% | - Salesforce Analytics Integration
- 1. Understand how Tableau Next integrates with Salesforce analytics platforms
- Tableau Next Apps and Marketplace
- 1. Understand how Tableau Next Apps for Salesforce and Marketplace offerings accelerate time to value
- Developer Tools and APIs
- 1. Describe tools and APIs available for developers
- Cross-Platform Workflows
- 1. Explain how Tableau Next assets are surfaced within user workflows across platforms
|
| Topic 4: Data Setup | 20% | - Semantic Models
- 1. Understand the components, design, and application of semantic models
- Data Architecture
- 1. Determine the appropriate data architecture or data processing approach for a given scenario
- Data 360
- 1. Understand basic Data 360 features and capabilities, including data integration, management, preparation, and modeling
|
| Topic 5: Managing Workspaces & Orgs | 10% | - Asset Deployment
- 1. Understand how to deploy Tableau Next assets
- Personal Org
- 1. Understand how to deploy and manage a Personal Org
- Asset Management and Sharing
- 1. Explain how to manage and share Tableau Next assets
|
| Topic 6: Agentic Experiences | 25% | - Analytics Agent
- 1. Understand how the Analytics Agent delivers proactive data alerts and notifications
- 2. Understand how the Analytics Agent enables users to explore data and generate insights
- Agentic Readiness
- 1. Explain how to assess and ensure Agentic readiness
- Generative AI
- 1. Understand how generative AI capabilities support the creation of Tableau Next components
|
>> Hot Analytics-Con-202 Questions <<
Analytics-Con-202 Actual Test & Analytics-Con-202 Exam Discount
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Salesforce Certified Tableau Next Consultant Sample Questions (Q46-Q51):
NEW QUESTION # 46
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?
- A. Data 360 Ingestion API
- B. Inbound and Outbound Change Sets
- C. Tableau Cloud Site Migration Tool
Answer: B
Explanation:
Among the listed choices, Inbound and Outbound Change Sets are the appropriate native Salesforce deployment mechanism. Tableau Next supports Salesforce Metadata API-based deployment capabilities, including change sets, for moving Tableau Next workspaces, visualizations, and dashboards between supported sandbox and target organizations. The workflow uses an outbound change set in the source org and an inbound change set in the target org.
The Data 360 Ingestion API is intended for bringing data into Data 360 rather than lifecycle deployment of Tableau Next metadata. The Tableau Cloud Site Migration Tool pertains to Tableau Cloud site migration and is not the Salesforce metadata deployment mechanism described here.
References/Topics: Managing Workspaces and Orgs - > Organize and Deploy Analytical Assets - > Deploy Tableau Next Assets.
NEW QUESTION # 47
A business analyst wants to quickly explore relationships between variables in Tableau Next without building a full dashboard. Which feature should they use?
- A. Data kits.
- B. Dashboard templates.
- C. Insights tab.
Answer: C
Explanation:
The Insights tab is the appropriate feature when an analyst wants to investigate relationships and patterns quickly without first constructing a complete dashboard. It provides an exploratory surface for examining analytical behavior, discovering notable patterns, and moving from a metric or measure into deeper investigation with less authoring overhead than a full dashboard workflow.
Dashboard templates are intended to standardize and accelerate dashboard creation. They are useful when a reusable dashboard structure is required, but they still relate to dashboard authoring rather than lightweight exploration. Data Kits serve a completely different lifecycle purpose: they package and deploy supported Tableau Next and Data 360 assets between environments.
The key distinction is therefore exploration versus construction and deployment. When the business question is still being investigated, the analyst should use Insights to understand relationships first. A dashboard can be created later when the analysis needs a curated, repeatable presentation for a broader audience.
References/Topics: Visualizations and Dashboards - > Insights - > Exploratory Analysis - > Metrics and Relationships.
NEW QUESTION # 48
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?
- A. Salesforce CLI
- B. Change Set
- C. Data Kit
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 # 49
A Tableau Next Consultant wants to use size encoding to highlight the volume of sales for products on a scatter plot. However, once the consultant builds the chart, they realize that the marks are overlapping and high- volume selling products are obscuring lower volume products. What should the consultant do to improve the visibility of the chart while highlighting differential sales volumes?
- A. Increase the size of the visualization on the dashboard so that the marks are more separated spatially.
- B. Adjust the minimum and maximum percentage of the cell the mark is allowed to occupy.
- C. Use a dual axis chart and place the volume of sales on the secondary axis.
Answer: B
Explanation:
Tableau Next provides explicit controls for size encoding, including minimum and maximum mark-size limits. With relative size encoding, Minimum (% of cell) defines the smallest percentage of available cell space that a mark can occupy, while Maximum (% of cell) controls the largest. Adjusting these settings allows the author to retain sales-volume encoding while limiting oversized marks that obscure smaller ones.
Therefore, B directly addresses the visualization problem.
A dual axis changes the structural representation of the data rather than correcting excessive mark sizing and is unnecessary for this requirement. Increasing the physical dashboard container size might provide additional display space, but it does not directly control the relative size range of the marks and cannot reliably prevent high-value marks from dominating lower-value marks.
Tableau Next supports both Relative and Absolute size modes. Relative sizing is particularly useful when the visual objective is to emphasize differences across a continuous measure while maintaining visual readability.
The consultant should tune the minimum and maximum percentage parameters until the volume relationship remains perceptible without excessive overlap.
References/Topics: Visualizations and Dashboards - > Marks - > Size Encoding - > Relative Size - > Minimum and Maximum Percent of Cell.
NEW QUESTION # 50
The client wants AI-generated insights about Gross Margin % in Tableau Next. Where is the best place to define this context for the agent?
- A. As a calculated field in the semantic model
- B. As a scoped dashboard calculated field
- C. As a Business Preference
Answer: C
NEW QUESTION # 51
......
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