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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and Prepare Data Connections | 22% | - Plan for data transformation
|
| Topic 2: Design and Troubleshoot Calculations and Workbooks | 40% | - Design visualizations and advanced analytics
|
| Topic 3: Evaluate Current State | 22% | - Evaluate current data structures
|
| Topic 4: Establish Governance and Support Published Content | 16% | - Deploy and manage content lifecycle
|
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NEW QUESTION # 64
A Tableau Next Consultant at Ursa Major Solar is creating a Tableau Next dashboard to monitor at- risk opportunities. The sales manager needs a way for sales reps to initiate follow- up tasks for specific opportunities directly from a dashboard widget. This action must trigger an existing Salesforce flow designed for task creation. Which action type should the consultant add to the widget to meet this requirement?
Answer: B
Explanation:
The consultant should configure a Salesforce Flow action on the dashboard widget. Tableau Next supports single-click dashboard actions that can directly initiate Salesforce Flows using dashboard context. Salesforce even documents a virtually identical use case: enabling sales representatives to create a follow-up task directly from a dashboard widget displaying at-risk opportunities.
When configuring the action, the consultant selects Salesforce Flow as the action type, chooses an eligible flow, and maps the flow's input variables to static or dynamic dashboard values. Tableau Next currently supports standard screen flows and autolaunched flows for this capability.
A parameter action is fundamentally an analytical interaction mechanism and is not the native mechanism for executing a Salesforce Flow. Option C refers generally to Salesforce actions on visualization records, but the scenario explicitly identifies a dashboard widget that must initiate an existing Salesforce Flow. The dedicated Flow action is therefore the precise implementation.
This capability illustrates Tableau Next's actionable-analytics design: the user moves directly from recognizing an analytical condition to initiating an operational Salesforce process without leaving the dashboard.
References/Topics: Visualizations and Dashboards - > Single-Click Actions - > Salesforce Flow Actions - > Dynamic Input Mapping.
NEW QUESTION # 65
A Tableau Next Consultant is asked to configure incremental refresh for a data source. Which limitation applies?
Answer: A
Explanation:
The documented limitation of Tableau Next Incremental Refresh for accelerated external connections is that it does not process deleted records. Salesforce states that an incremental refresh updates cached data with records that have been added or changed since the previous refresh, but deleted source data is not updated in the cache.
Consequently, options B and C are incorrect. Inserts are specifically part of incremental processing, as are updates to existing records. The limitation applies only to deletions.
This matters architecturally when data freshness requirements include removal of records. If the external source deletes a transaction, customer, product, or other row, repeated incremental refreshes can leave the old cached representation present. A Full Refresh is required to reconcile the cache completely because full refresh deletes the existing cached dataset and replaces it with a fresh source dataset.
Consultants should therefore choose refresh mode based on more than refresh frequency. Incremental refresh is efficient and can run frequently, but Full Refresh is required when complete source-state reconciliation, including deletions, is a business requirement.
References/Topics: Data Setup - > Data Acceleration - > Incremental Refresh - > Full Refresh - > Deleted- Record Handling.
NEW QUESTION # 66
A business analyst wants to quickly explore relationships between variables in Tableau Next without building a full dashboard. Which feature should they use?
Answer: A
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 # 67
The client wants AI-generated insights about Gross Margin % in Tableau Next. Where is the best place to define this context for the agent?
Answer: B
Explanation:
For agent-specific business context about how Gross Margin % should be understood or interpreted, Business Preferences are the best choice. Salesforce uses Business Preferences to add organization-specific knowledge and instructions to a semantic model so Tableau Agent can interpret users' analytical questions according to the organization's terminology and business logic.
A calculated field is appropriate when Gross Margin % itself must be mathematically derived-for example, (Revenue - Cost) / Revenue. However, the question does not ask where to implement the mathematical calculation; it asks where to define context for AI-generated insights. Contextual instructions, such as what
"healthy gross margin" means or which business interpretation to apply, belong in Business Preferences.
A dashboard-scoped calculated field is even less suitable because it confines logic to a specific downstream analytical artifact instead of enriching the governed semantic context used by Tableau Agent across conversational experiences.
Salesforce's broader semantic architecture reinforces this separation: semantic models provide standardized business logic and definitions, while Business Preferences augment those models with business-specific interpretive knowledge for conversational analytics.
References/Topics: Agentic Experiences - > Business Preferences - > Tableau Agent Context - > Semantic Model Enrichment.
NEW QUESTION # 68
A Tableau Next Consultant is asked to configure streaming data ingestion. Where is the output written?
Answer: B
Explanation:
A Data Stream Object (DSO) is the output associated with streaming data ingestion in this question.
Streaming ingestion is designed to continuously accept incoming records from a connected source and represent that stream in Data 360 so downstream processing and analytics can work with newly arriving data with minimal delay.
A Data Lake Object is used as a persisted data-layer object for broader ingestion and storage scenarios, while a Semantic Model is a downstream analytical abstraction that defines business-friendly measures, dimensions, relationships, metrics, and other semantic logic. Neither option describes the streaming-ingestion output requested by this item.
The exam distinction is to keep the ingestion pipeline separate from the semantic layer. Streaming data first enters through the streaming/data-stream construct, where the Data Stream Object represents the incoming stream. That data can then participate in downstream mapping, modeling, and Tableau Next analytics. The semantic model does not serve as the raw ingestion target; it consumes prepared and governed data structures to provide analytical meaning.
References/Topics: Data Setup - > Streaming Data Ingestion - > Data Stream Objects.
NEW QUESTION # 69
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