Analytics-Con-202 Exam Prep & Analytics-Con-202 Study Guide & Analytics-Con-202 Actual Test

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Salesforce Analytics-Con-202 Exam Syllabus Topics:

SectionWeightObjectives
Data Setup20%- Data 360
  • 1. Understand basic Data 360 features and capabilities, including data integration, management, preparation, and modeling
    - Semantic Models
    • 1. Understand the components, design, and application of semantic models
      - Data Architecture
      • 1. Determine the appropriate data architecture or data processing approach for a given scenario
        Managing Workspaces & Orgs10%- Asset Deployment
        • 1. Understand how to deploy Tableau Next assets
          - Personal Org
          • 1. Understand how to deploy and manage a Personal Org
            - Asset Management and Sharing
            • 1. Explain how to manage and share Tableau Next assets
              Visualizations & Dashboards15%- Dashboard Actions
              • 1. Explain how to configure actions within Tableau Next
                - Visualization and Dashboard Design
                • 1. Apply visualization and dashboarding best practices to design user-friendly Tableau Next assets
                  Basic Setup & Admin10%- Tableau Next Activation and Management
                  • 1. Explain how to activate and manage Tableau Next features
                    - Access Management
                    • 1. Identify and apply appropriate access to enable users
                      - Agentic Analytics
                      • 1. Describe how to activate Agentic Analytics for users
                        Agentic Experiences25%- Generative AI
                        • 1. Understand how generative AI capabilities support the creation of Tableau Next components
                          - Analytics Agent
                          • 1. Understand how the Analytics Agent enables users to explore data and generate insights
                            • 2. Understand how the Analytics Agent delivers proactive data alerts and notifications
                              - Agentic Readiness
                              • 1. Explain how to assess and ensure Agentic readiness
                                Embedding, Cross-Cloud, & Interoperability20%- Developer Tools and APIs
                                • 1. Describe tools and APIs available for developers
                                  - Tableau Next Apps and Marketplace
                                  • 1. Understand how Tableau Next Apps for Salesforce and Marketplace offerings accelerate time to value
                                    - Salesforce Analytics Integration
                                    • 1. Understand how Tableau Next integrates with Salesforce analytics platforms
                                      - Cross-Platform Workflows
                                      • 1. Explain how Tableau Next assets are surfaced within user workflows across platforms

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                                        Salesforce Certified Tableau Next Consultant Sample Questions (Q20-Q25):

                                        NEW QUESTION # 20
                                        A Tableau Next Consultant is advising a customer on when to use Tableau Agent versus building a traditional Tableau Next dashboard. Which scenario is the best fit for Tableau Agent?

                                        Answer: C

                                        Explanation:
                                        Tableau Agent is optimized for conversational, exploratory analytics in which a business user asks natural- language questions and receives grounded answers and visualizations. A request such as, "What are my top accounts by Annual Contract Value this quarter?" maps directly to Tableau Agent's supported descriptive- analysis capabilities. Salesforce explicitly lists Top-N questions, aggregations, dimensional breakdowns, comparisons, and other business-oriented analytical questions among the supported conversational patterns.
                                        A fixed monthly-close report for a board is better represented by a governed dashboard or reporting asset because its structure, presentation, and recurring content are predetermined. Likewise, Tableau Agent is not positioned as a general-purpose data-science workflow development environment.
                                        The architectural distinction is important for the exam: dashboards provide curated, repeatable analytical experiences, whereas Tableau Agent adds an interactive conversational layer over semantic models. It translates the user's business question into semantic analytical operations and returns contextual text and visual output.
                                        References/Topics: Agentic Experiences - > Analyze and Share Data in Tableau Next - > About Conversational Analytics - > Supported Questions and Surfaces.


                                        NEW QUESTION # 21
                                        Cloud Kicks (CK) is designing a unified Customer 360 semantic data model (SDM). CK requires strict row level security (RLS) so that regional sales managers can only query and view accounts within their assigned territories. What is the recommended best practice for enforcing this security requirement in Tableau Next?

                                        Answer: B

                                        Explanation:
                                        Tableau Next row-level security should be implemented through Data 360 governance policies, making B correct. Salesforce explicitly states that for Data 360 DLOs and DMOs, record-level security is defined through Data 360 policies. Tableau Next dashboards and visualizations built on those objects then inherit the enforced data visibility.
                                        For example, the account dataset can include an attribute identifying the responsible territory or regional manager. A Data Governance access policy can evaluate the current user's relevant attributes and restrict returned records accordingly. Because security is enforced below the semantic and visualization layers, the same rules consistently protect dashboards, metrics, Tableau Agent queries, and other downstream consumers.
                                        Option A describes the traditional Tableau USERNAME() pattern, but current Tableau Next guidance explicitly states that native user functions such as USERNAME() aren't the preferred/current RLS implementation for this architecture. Option C creates serious scalability, maintenance, and consistency problems and violates centralized governance principles.
                                        The architectural rule is: define security as close to the governed data layer as possible so every downstream analytical experience inherits the same policy.
                                        References/Topics: Data Setup - > Data 360 Governance - > Row-Level Security - > Access Policies - > Data Object Security.


                                        NEW QUESTION # 22
                                        A Tableau Next Consultant is asked to configure proactive alerts for pipeline metrics. Which license type is required to set alerts?

                                        Answer: C

                                        Explanation:
                                        A Creator license is required to set proactive alerts for pipeline metrics in the scenario described. Creating an alert is more than passive consumption: the user defines a monitored condition, configures when that condition should trigger, and establishes an ongoing analytical action against the governed metric. Those capabilities fall within the Creator-level analytical configuration persona.
                                        A Consumer can view and interact with published analytical content but does not receive the complete authoring and configuration privileges associated with creating alert definitions. The Viewer choice is even more limited and does not provide the required proactive-alert setup capability. Therefore, assigning Creator access is the appropriate licensing decision for users who must establish their own alerts.
                                        The broader certification principle is to align licenses with the user's intended role. Users who only consume metrics should remain on the consumption tier, while users who need to create or configure analytical behavior-including proactive alert definitions-require the higher authoring entitlement. This separates governance and cost while ensuring that only appropriately licensed users can create monitoring rules.
                                        References/Topics: Agentic Experiences - > Proactive Data Alerts - > Creator License Requirements.


                                        NEW QUESTION # 23
                                        A Tableau Next Consultant is asked to configure semantic models for sales and service data. What is the benefit of semantic models?

                                        Answer: B

                                        Explanation:
                                        The fundamental purpose of Tableau Semantics is to establish consistent, governed business definitions that can be reused across analytical and AI experiences. Salesforce describes semantic models as the place where organizations define and govern business metrics, relationships, dimensions, calculations, and familiar business terminology.
                                        This means sales and service teams can use the same authoritative definitions rather than implementing independent calculations within each dashboard. For example, concepts such as Annual Recurring Revenue, Case Resolution Time, Customer Lifetime Value, or Gross Margin can be defined centrally and then reused across dashboards, metrics, Tableau Agent conversations, and other Data 360-powered experiences.
                                        Option B is far too narrow. Semantic models can support efficient query generation, but their primary benefit is not merely dashboard rendering performance.
                                        Option C is also incorrect. Tableau Next inherits RLS and other governance controls from Data 360 security policies; a semantic model does not automatically create record-level security simply by existing.
                                        The exam principle is: Tableau Semantics = reusable, centrally governed meaning, ensuring humans, dashboards, metrics, and AI reason from the same business definitions.
                                        References/Topics: Data Setup - > Tableau Semantics - > Semantic Models - > Single Source of Truth - > Standardized Business Logic.


                                        NEW QUESTION # 24
                                        A Tableau Next Consultant wants to implement a Tableau Agent within Tableau Next to provide conversational insights and automated chart summaries for its sales operations managers. The deployment strategy requires using a preconfigured platform framework to accelerate the setup. How should the consultant deploy this specific conversational analytics capability?

                                        Answer: B

                                        Explanation:
                                        Tableau Agent conversational analytics is delivered through the Analytics and Visualization agent template.
                                        Salesforce's current documentation states that enabling Tableau Agent makes the Analytics and Visualization template and its prebuilt capabilities available in Agentforce Builder or Agentforce Studio. The consultant then creates an agent from that template and includes the Data Analysis subagent to enable conversational analytical responses and generated visualizations.
                                        Therefore, B is correct.
                                        Einstein Discovery Prediction is associated with predictive analytics and is not the preconfigured framework for Tableau Agent's conversational analytics. Tableau Next Marketplace contains reusable analytical assets and templates but is not the mechanism for constructing the core Analytics and Visualization agent.
                                        References/Topics: Agentic Experiences - > Tableau Agent - > Analytics and Visualization Template - > Data Analysis Subagent - > Conversational Analytics.


                                        NEW QUESTION # 25
                                        ......

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