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| Section | Weight | Objectives |
|---|---|---|
| Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Managing Workspaces & Orgs | 10% | - Personal Org
|
| Basic Setup & Admin | 10% | - Agentic Analytics
|
| Agentic Experiences | 25% | - Generative AI
|
| Data Setup | 20% | - Semantic Models
|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Salesforce Analytics Integration
|
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NEW QUESTION # 10
A Tableau Next Consultant needs to ensure that dashboards are branded consistently across all workspaces.
Which feature should be used?
Answer: A
Explanation:
Org-wide custom color palettes provide the appropriate mechanism for maintaining consistent dashboard branding across workspaces. A centrally defined palette establishes approved organizational colors that dashboard authors can reuse instead of choosing arbitrary colors independently for each asset. This improves brand consistency and also reduces visual ambiguity when the same categories, statuses, or business concepts appear across multiple dashboards.
Dashboard templates can standardize layout and content structure, but the requirement is specifically consistent branding across all workspaces, not merely reuse of one dashboard design. Workspace themes are not the designated answer for organization-wide color standardization in this question. The palette is the reusable branding control that directly addresses consistent color usage.
A consultant should treat color as governed presentation metadata. Approved colors can reflect corporate identity, accessibility requirements, and established semantic conventions-for example, standardized colors for warning, success, and critical states. Using a common palette across analytical assets creates a coherent visual language while still allowing individual dashboards to differ in layout and analytical purpose.
References/Topics: Visualizations and Dashboards - > Org-Wide Custom Color Palettes - > Consistent Branding.
NEW QUESTION # 11
A Tableau Next Consultant is asked to configure batch data transforms. Where is the output written?
Answer: B
Explanation:
Data Lake Object (DLO) is the correct answer among the available choices. A Data 360 Batch Data Transform requires an Output node where the transformed results are persisted. Salesforce documents that a Batch Data Transform can write its results to a new or existing target Data Lake Object, which can subsequently serve as input to identity resolution, calculated insights, segmentation, semantic modeling, or additional transforms.
A Data Stream Object is not the destination used to persist transformed output. Data streams provide ingestion pipelines that bring source data into Data 360. A Semantic Data Model is also not the physical output storage target; Tableau Semantics consumes governed Data 360 objects to provide measures, dimensions, relationships, calculations, and business context.
References/Topics: Data Setup - > Data 360 - > Batch Data Transforms - > Output Nodes - > Data Lake Objects.
NEW QUESTION # 12
A mature Tableau customer wants to use the Analytics Agent in Tableau Next. However, they have heavily invested in complex data models and calculations within Tableau Cloud Published Data Sources (PDSs) and refuse to rebuild this logic from scratch in Data 360. How should a Tableau Next Consultant meet this requirement using native interoperability?
Answer: C
Explanation:
Tableau Next provides native interoperability with Tableau Cloud Published Data Sources (PDSs). Salesforce allows a consultant to create a Data 360 semantic model by connecting directly to an existing PDS after establishing the required trust between the Salesforce org and Tableau Cloud site.
The PDS remains the external data definition and query source. Tableau Next inherits fields such as their names and data types, and the semantic model can then be enriched with calculated fields, metrics, descriptions, and business context. Critically, Salesforce states that this approach allows organizations to use existing Tableau content without data or metadata migration.
That precisely addresses the customer's concern about preserving substantial prior investment in Tableau Cloud modeling and calculations.
Options A and B introduce mechanisms that are not the native Tableau Next interoperability pattern documented for PDS reuse. There is no requirement to translate the PDS into Snowflake SQL or convert it into a CRM Analytics recipe.
This architecture enables Tableau Next to extend rather than replace mature Tableau investments, while exposing existing governed analytical logic to Tableau Agent.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Cloud PDS - > Tableau Semantics - > Create Semantic Model from Published Data Source.
NEW QUESTION # 13
A team at Universal Containers collaborates frequently in Slack. The goal is to share a Tableau Next metric within a Slack canvas, ensuring it appears as a rich preview where the data regularly refreshes for each team member. All team members have appropriately assigned licenses. Which procedure should a Tableau Next Consultant instruct a user to follow to achieve this?
Answer: B
Explanation:
For a live Tableau Next preview inside a Slack canvas, Salesforce instructs users to paste the Tableau Next asset URL into the canvas and select Card from the Paste As menu. The resulting card can display a metric, dashboard, or visualization and regularly refresh its underlying data.
This behavior differs materially from sharing a static Tableau Next preview in an ordinary Slack channel or direct message. In a Canvas, Salesforce retrieves the data from each viewer's perspective. Consequently, each person must have appropriate Tableau Next access to the underlying asset and data. Unauthorized users receive an access message instead of seeing protected data. This preserves individual data governance while still providing a rich collaborative experience.
Option A does not describe the documented Slack Canvas workflow. Option C produces a static image and therefore fails the requirement for regularly refreshed information.
The exam distinction is important: standard Slack message preview = snapshot governed by sharing behavior; Slack Canvas Card = live, refreshable preview evaluated against each viewer's access.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next in Slack - > Slack Canvas - > Paste As Card - > Viewer-Based Data Access.
NEW QUESTION # 14
A Tableau Next Consultant has developed a dashboard using a single semantic model. The dashboard includes filters, metrics, and visualizations. The consultant wants to be able to make changes to their filters and selections in their visualizations that update the metrics. They are already able to filter visualizations between each other by clicking into the views and using the filters on the page. What does the consultant need to validate to have the desired functionality?
Answer: A
Explanation:
For a Tableau Next Metric widget to respond dynamically to dashboard filtering, two conditions must be satisfied. First, the metric widget must be configured to receive dashboard filters. Second, the dimensions being used by those dashboard filters must exist in the metric definition as supported dimensions. Salesforce specifically documents that a Metric widget can only be filtered by dimensions explicitly included in the metric definition, typically as Additional Dimensions.
Therefore, C is the only complete answer.
Option A fails because enabling dashboard-filter reception is not enough if the metric definition lacks the necessary dimensions. Tableau Next cannot apply a filter against a dimensional grain the metric does not expose. Option B has the required dimensions but explicitly disables receipt of dashboard filters, preventing the widget from responding to dashboard interactions.
This distinction is important because visualizations and metric widgets have different interaction requirements. A dashboard visualization can participate naturally in interactive filtering, whereas a governed metric must expose the appropriate dimensions in its semantic definition before those dashboard selections can alter the displayed metric result.
References/Topics: Visualizations and Dashboards - > Metric Widgets - > Receive Dashboard Filters - > Metric Additional Dimensions.
NEW QUESTION # 15
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