Die Prüfungsfragen und Antworten zur Salesforce Analytics-Con-202 Zertifizierungsprüfung von Zertpruefung wird von unserem Expertenteam nach ihren umfangreichen Kenntnissen und Erfahrungen berarbeitet. Sie können die Bedürfnisse der Kandidaten abdecken. Sie finden vielleicht in anderen Büchern oder auf anderen Websites auch die Salesforce Analytics-Con-202 Schulungsunterlagen. Aber die Schulungsunterlagen von Zertpruefung sind die umfassendste unter ihnen und zugleich kann Ihnen die beste Garantie geben. Bitte wählen Sie die Salesforce Analytics-Con-202 Prüfungsfragen und Antworten von Zertpruefung.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Agentic Experiences | 25% | - Agentic Readiness
|
| Topic 2: Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Topic 3: Basic Setup & Admin | 10% | - Tableau Next Setup
|
| Topic 4: Data Setup | 20% | - Data Architecture and Processing
|
| Topic 5: Managing Workspaces & Orgs | 10% | - Personal Org
|
| Topic 6: Embedding, Cross-Cloud, & Interoperability | 20% | - Developer Tools and APIs
|
>> Analytics-Con-202 Zertifizierungsprüfung <<
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41. Frage
During a Tableau Next implementation, a Tableau Next Consultant is explaining to the admin team when Agent Scoping for Tableau Agent actually takes effect. When is Agent Scoping used?
Antwort: C
Begründung:
Agent Scoping is specifically designed for situations in which Tableau Agent receives a question without clear analytical context. Salesforce defines Agent Scoping as the administrator-controlled list of semantic models that Tableau Agent can search when context cannot otherwise determine which model should answer the user's question.
Typical examples include Tableau Agent being used in Slack or embedded on a page that does not contain a Tableau Next dashboard, metric, or other asset capable of supplying context. The configured semantic-model list serves as a fallback list. Tableau Agent can then determine which approved model should be used to resolve the user's request.
Agent Scoping does not run indiscriminately for every question, which eliminates B. When Tableau Agent is invoked from an analytical surface that already provides clear semantic context, that existing context guides the interaction. C is also overly restrictive; Agent Scoping is not limited to metric-details pages or scenarios involving multiple models attached to a metric.
Administrators can configure approved fallback semantic models for active Analytics and Visualization agents using the Data Analysis subagent.
References/Topics: Agentic Experiences - > Tableau Agent - > Agent Scoping - > Fallback Semantic Models
- > Context Resolution.
42. Frage
A Tableau Next Consultant is asked to configure incremental refresh for a data source. Which limitation applies?
Antwort: B
Begründung:
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.
43. Frage
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?
Antwort: A
Begründung:
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.
44. Frage
A Tableau Next Consultant has created a new semantic model and wants to identify potential metadata gaps that might confuse the Analytics Agent. Which tool provides an automated "Readiness Score" and actionable suggestions to improve the model's clarity for the AI?
Antwort: A
Begründung:
Optimize Model is the feature designed to assess semantic models for AI readiness and recommend improvements. Salesforce describes Semantic Model AI Optimization as evaluating model quality, diagnosing problems, and supplying guided remediation that improves reliability for Tableau Agent. After the feature is enabled, an Optimize Model indicator appears in Semantic Model Builder and shows the model's AI-readiness strength.
Opening the Optimize Model panel provides a breakdown of AI-readiness indicators together with recommended corrective actions. The rating is recalculated as the semantic model changes, allowing consultants to iteratively improve metadata, structure, and agent compatibility.
Q & A Calibration serves a different purpose: it tests representative natural-language questions and helps calibrate how Tableau Agent responds. Business Preferences provide explicit business context and rules, such as how ambiguous terminology should be interpreted. Neither performs the automated holistic readiness evaluation described in the question.
References/Topics: Data Setup - > Semantic Model AI Optimization - > Optimize Model - > AI-Readiness Strength - > Recommended Actions.
45. Frage
Before launching a dashboard in Tableau Next, a Tableau Next Consultant gives the appropriate team View access to the dashboard's workspace. Which other access consideration should the consultant verify before rolling this dashboard out to end users?
Antwort: A
Begründung:
Tableau Next asset sharing and Data 360 data access are separate layers. Granting users Viewer access to a workspace can provide inherited access to its dashboards, visualizations, and semantic models, but it does not automatically grant access to the underlying Data 360 data. Salesforce explicitly states that access to a semantic model requires access to the data space containing the model as well as access to the objects and fields used by that model.
Therefore, C is correct.
End users do not require Edit access to underlying Data 360 objects merely to view dashboard data, making A unnecessarily privileged. Similarly, B is incorrect because Consumer-level permission sets can view Tableau Next assets; Platform Analyst or Self-Service Analyst permissions are not universally required for dashboard consumption.
The architecture can be understood as three layers: license/permission access, Tableau Next asset sharing, and Data 360 data visibility/governance. Successful dashboard rollout requires all applicable layers to authorize the user. Sharing alone cannot override an administrator's data-space, DMO, DLO, field, or policy restrictions.
References/Topics: Managing Workspaces and Orgs - > Asset Sharing - > Data Spaces - > Data 360 Governance - > Semantic Model Access.
46. Frage
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Analytics-Con-202 Buch: https://www.zertpruefung.de/Analytics-Con-202_exam.html