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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Embedding, Cross-Cloud, & Interoperability | 20% | - Developer Tools and APIs
|
| Topic 2: Basic Setup & Admin | 10% | - User Access
|
| Topic 3: Managing Workspaces & Orgs | 10% | - Personal Org
|
| Topic 4: Visualizations & Dashboards | 15% | - Visualization and Dashboard Design
|
| Topic 5: Agentic Experiences | 25% | - Generative AI
|
| Topic 6: Data Setup | 20% | - Data Architecture and Processing
|
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Hence, memorizing them will help you get prepared for the Salesforce Analytics-Con-202 examination in a short time. The product of PracticeMaterial comes in PDF, desktop practice exam software, and Salesforce Certified Tableau Next Consultant (Analytics-Con-202) web-based practice test. To give you a complete understanding of these formats, we have discussed their features below.
NEW QUESTION # 77
A Tableau Next Consultant shares a metric in Slack that contains sensitive data governed by Data 360 policies. A user who does not have a Tableau Next license views the shared message in Slack and can see the metric image. The consultant is concerned there's a problem with the data security setup. Which statement correctly describes this behavior?
Answer: A
Explanation:
For a standard Tableau Next Slack message preview, Salesforce explicitly warns that anyone who can see the Slack message can see its preview, including filters applied when it was shared. Consequently, users should verify that the preview does not expose inappropriate sensitive information before posting it into a channel or conversation.
Tableau Next's Slack integration generates previews according to the sender's permission access and Tableau Next governance context. Once that snapshot-style preview is shared, visibility of the message governs who can see that static representation.
Therefore, C correctly describes the behavior. There is no indication that Data 360 security has malfunctioned.
Option A is wrong because recipients do not automatically obtain unrestricted interactive access to the underlying Tableau Next asset. Option B incorrectly assumes that each static Slack preview is dynamically authorization-checked as though the recipient were opening Tableau Next.
A critical distinction is that Slack Canvas cards behave differently: Canvas previews can refresh using each viewer's Tableau Next access, and unauthorized users cannot see the live underlying content.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next in Slack - > Shared Previews - > Governance.
NEW QUESTION # 78
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 # 79
Universal Containers wants to ensure its users are able to view, explore, and follow metrics. What is the minimum license level that grants this ability?
Answer: A
Explanation:
The minimum general Tableau Next persona that can view, explore, and follow metrics is the Tableau Unmetered Consumer level represented by B.
Salesforce documents that Consumer users can access the Tableau Next home experience, use Tableau Agent, view workspaces, dashboards, and visualizations, and view, explore, and follow metrics. Salesforce's metric- specific documentation likewise identifies Tableau Unmetered Consumer and equivalent Consumer/Self- Service Consumer permission sets as sufficient to follow metrics.
A Self-Service Analyst can also perform these actions, but that persona includes significantly broader capabilities and therefore is not the minimum required level. Analysts can work with Tableau Next Studio and, depending on the permission set, create or edit analytical content.
An Included App license is narrower. Included App/Limited Consumer personas are designed primarily to interact with prepackaged Tableau Next Apps for Salesforce rather than provide general Tableau Next home and metric exploration capabilities.
The exam principle is to select the least-privileged persona that fully satisfies the requirement, rather than assigning authoring permissions merely because they also include consumption capabilities.
References/Topics: Basic Setup and Admin - > Tableau Next Licenses and Permission Sets - > Consumer - > Metric Exploration and Following.
NEW QUESTION # 80
A Tableau Next Consultant faces a requirement calling for data pivots, aggregations, and calculations to the data before pulling it into a semantic data model (SDM). Which Data 360 feature should the consultant use to create a data object with these data adjustments?
Answer: B
Explanation:
Batch Data Transforms are designed to perform repeatable data-shaping operations before downstream analytical consumption. Salesforce describes batch transforms as canvas-based processing flows capable of adding, manipulating, joining, aggregating, filtering, and applying formulas or other transformations to data before writing the resulting dataset to a target object.
This makes A the appropriate solution when the requirement involves multiple structural transformations- such as pivots, aggregations, and calculations-before the resulting dataset becomes part of a semantic model.
Identity Resolution solves a different problem: reconciling and matching records across data sources to build unified profiles. It does not provide the generalized transformation pipeline required here.
Calculated fields can create derived values, but they are insufficient when the preparation requirement involves broad reshaping and aggregation of the underlying dataset. The transformations should occur at the Data 360 data-preparation layer, after which the output object can be used by downstream analytics.
Batch transforms can write to supported DLO or DMO output nodes depending on the source and design, providing a persistent transformed object that semantic modeling and other Data 360 processes can consume.
References/Topics: Data Setup - > Data 360 - > Batch Data Transforms - > Aggregate, Join, Transform, and Output Nodes.
NEW QUESTION # 81
A Tableau Next Consultant is asked to configure streaming data ingestion. Where is the output written?
Answer: A
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 # 82
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