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| Section | Weight | Objectives |
|---|---|---|
| Embedding, Cross-Cloud, & Interoperability | 20% | - Tableau Next Apps and Marketplace
|
| Basic Setup & Admin | 10% | - User Access
|
| Managing Workspaces & Orgs | 10% | - Workspace and Asset Management
|
| Visualizations & Dashboards | 15% | - Dashboard Actions
|
| Data Setup | 20% | - Semantic Models
|
| Agentic Experiences | 25% | - Agentic Readiness
|
２１世紀の情報時代の到着に伴い、SalesforceのAnalytics-Con-202試験の認定はIT業種で不可欠な認定になっています。初心者にしても、サラリーマンにしても、Jpshikenは君のために特別なSalesforceのAnalytics-Con-202問題集を提供します。君は他の人の一半の努力で、同じSalesforceのAnalytics-Con-202認定試験を簡単に合格できます。Jpshikenはあなたと一緒に君のITの夢を叶えるために頑張ります。まだなにを待っていますか。
質問 # 79
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?
正解：C
質問 # 80
The client wants AI-generated insights about Gross Margin % in Tableau Next. Where is the best place to define this context for the agent?
正解：C
質問 # 81
Cloud Kicks (CK) has created a semantic model and associated metrics to help improve the conversion rate for marketing driven leads. Sales and marketing teams both regularly review these metrics. When reviewing the project's results, CK discovers that both teams are looking at the same metrics, but often have parallel discussions in Slack without awareness of the other's conversation. Which functionality of Tableau Next in Slack should a Tableau Next Consultant highlight to improve cross- team collaboration?
正解：C
解説：
The Conversations tab is specifically designed to expose related Slack discussions associated with Tableau Next analytical assets. When a Tableau Next metric, dashboard, or visualization is shared in Slack, users can open its preview and select Conversations to browse related Slack channels, threads, or direct-message discussions that they are authorized to access.
This directly addresses the scenario: sales and marketing are already discussing the same analytical content, but those discussions are fragmented. Surfacing related conversations in the asset context enables teams to discover existing dialogue instead of unknowingly creating duplicate parallel threads.
Option A changes how metrics are surfaced but does not address visibility into conversations already occurring around those metrics. Option C creates yet another broadcast mechanism and does not consolidate or expose existing contextual discussions.
A key design point is that Slack permissions continue to apply. The Conversations tab does not reveal conversations that the current user is unauthorized to access. Instead, it creates analytical context across conversations the user can already legitimately view, preserving Slack security while improving cross-team awareness.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next in Slack - > Related Conversations - > Conversations Tab.
質問 # 82
During a discovery call, a client tells their Tableau Next Consultant that they love the idea of embedding the Analytics and Visualization Agent into an external portal, but that they have three dashboards on the same page: Sales Performance, Risk Exposure, and Regional Revenue. What is true about the agent's capabilities in this scenario?
正解：C
解説：
The Tableau Next Analytics Embedding SDK supports an AnalyticsAgent component with both single- context and multi-component operating modes. In Multi-Component mode, the application omits the contextConfig property. The agent then automatically tracks the embedded AnalyticsDashboard and AnalyticsMetric components present on that page.
Therefore, B directly describes the intended architecture for a portal containing multiple analytical components.
Option A describes single-context mode, where contextConfig explicitly binds the agent to one dashboard, metric, or semantic model. That mode exists but is not a platform limitation. Option C introduces a same- semantic-model restriction that the current Embedding SDK documentation does not impose. The SDK explicitly describes automatic context tracking across embedded dashboard and metric components.
This capability is particularly important in embedded analytics because it allows conversational analytics to understand the broader analytical surface rather than forcing the external application to continually rebind the agent as users move between embedded components.
References/Topics: Embedding, Cross-Cloud, and Interoperability - > Tableau Next Embedding SDK - > AnalyticsAgent - > Multi-Component Mode.
質問 # 83
A Tableau Next Consultant needs to migrate dashboards from a sandbox org to production. Which deployment mechanism should be used?
正解：C
解説：
Data Kits are a native supported deployment mechanism for moving Tableau Next assets from a sandbox to a production Data 360 home org. Salesforce explicitly states that Tableau Next workspaces, visualizations, and dashboards can be deployed through Data Kits, and that Data 360 semantic models on which those analytical assets depend must also use Data Kits for deployment to target home orgs.
CSV export/import is a data-transfer technique, not a Tableau Next metadata lifecycle-management mechanism. It cannot preserve dashboard structure, visualization definitions, semantic-model dependencies, workspace metadata, or the relationships between these assets. Manual recreation would be operationally inefficient, prone to configuration drift, and unnecessary when supported deployment tooling exists.
A technically complete implementation must also account for dependency sequencing. When a Data Kit contains the semantic model and downstream Tableau Next content, Salesforce requires the publishing order to be at least Semantic Models - > Workspaces - > Visualizations - > Dashboards.
References/Topics: Managing Workspaces and Orgs - > Sandbox Development - > Data Kits - > Production Deployment - > Asset Dependencies.
質問 # 84
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専門家と他の作業スタッフの熱心な献身により、当社のAnalytics-Con-202学習教材はより成熟し、困難に立ち向かうことができます。 Analytics-Con-202準備試験は、業界で高い合格率を達成しており、Analytics-Con-202試験問題では、絶え間ない努力で常に99％の合格率を維持しています。私たちは、このようなスターのような人物の背後に、当社からの大量投資を受け入れていることを認めなければなりません。当社の設立以来、私たちはAnalytics-Con-202試験資料に大量の人材、資料、資金を投入しました。
Analytics-Con-202関連日本語版問題集: https://www.jpshiken.com/Analytics-Con-202_shiken.html