Fully Updated Salesforce Analytics-Con-202 Dumps With Latest Analytics-Con-202 Exam Questions [2026]

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Salesforce Analytics-Con-202 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Agentic Experiences25%- Generative AI
  • 1. Generative AI capabilities for creating Tableau Next components
    - Agentic Readiness
    • 1. Assess and ensure Agentic readiness
      - Analytics Agent
      • 1. Proactive data alerts and notifications
        • 2. Explore data and generate insights
          Topic 2: Basic Setup & Admin10%- Tableau Next Setup
          • 1. Activate and manage Tableau Next features
            - Agentic Analytics
            • 1. Activate Agentic Analytics for users
              - User Access
              • 1. Apply appropriate access to enable users
                Topic 3: Managing Workspaces & Orgs10%- Personal Org
                • 1. Deploy and manage a Personal Org
                  - Workspace and Asset Management
                  • 1. Deploy Tableau Next assets
                    • 2. Manage and share Tableau Next assets
                      Topic 4: Visualizations & Dashboards15%- Dashboard Actions
                      • 1. Configure actions within Tableau Next
                        - Visualization and Dashboard Design
                        • 1. Design user-friendly Tableau Next assets
                          • 2. Visualization and dashboarding best practices
                            Topic 5: Embedding, Cross-Cloud, & Interoperability20%- Developer Tools and APIs
                            • 1. Tools and APIs available for developers
                              - Cross-Platform Workflows
                              • 1. Surface Tableau Next assets within user workflows across platforms
                                - Tableau Next Apps and Marketplace
                                • 1. Marketplace offerings
                                  • 2. Tableau Next Apps for Salesforce
                                    - Salesforce Analytics Integration
                                    • 1. Tableau Next integration with Salesforce analytics platforms
                                      Topic 6: Data Setup20%- Data 360
                                      • 1. Data integration, management, preparation, and modeling
                                        - Data Architecture and Processing
                                        • 1. Determine the appropriate data architecture or data processing approach
                                          - Semantic Models
                                          • 1. Components, design, and application of semantic models

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                                            Salesforce Certified Tableau Next Consultant Sample Questions (Q57-Q62):

                                            NEW QUESTION # 57
                                            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 # 58
                                            What is a logical view within a semantic data model?

                                            Answer: A

                                            Explanation:
                                            A Logical View is a semantic data object that combines underlying objects through explicitly configured joins or unions and presents the resulting structure as a single analytical object. Of the choices provided, A correctly captures this concept: the view contains participating objects whose join structure and relationship characteristics must be defined.
                                            Salesforce's current glossary defines a Logical View as a data object that combines multiple tables using special joins and then allows that enriched dataset to be queried as one object. It can subsequently participate in calculated fields, metrics, semantic relationships, and other definitions.
                                            Proper cardinality is important because Tableau Semantics must know whether objects relate one-to-one, one- to-many, many-to-one, or many-to-many to prevent duplicate aggregation or missing results. Salesforce provides explicit cardinality configuration for semantic relationships.
                                            Option B confuses a Logical View with ordinary semantic relationships inherited or defined among data objects. Option C describes neither the structure nor purpose of Logical Views.
                                            The critical exam distinction is relationships preserve separate objects, while a Logical View combines objects into a single logical analytical structure.
                                            References/Topics: Data Setup - > Tableau Semantics - > Logical Views - > Joins - > Cardinality.


                                            NEW QUESTION # 59
                                            A Tableau Next Consultant is asked to configure incremental refresh for a data source. Which limitation applies?

                                            Answer: B

                                            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 # 60
                                            A data analyst at Cloud Kicks has been tasked with creating and sharing Tableau Next assets, including workspaces and dashboards. The user also needs to manage a Personal Org. They have been assigned a Tableau Next Creator license. Which permission set should a Tableau Next Consultant assign to this user to fulfill these requirements?

                                            Answer: A

                                            Explanation:
                                            Salesforce guidance states that a Tableau Next Self-Service Analyst requires a Tableau Next Creator license and provides access to Tableau Next Studio, Tableau Agent, Personal Org ownership, analytical assets, and self-service creation/editing functionality within the Personal Org. Personal Org owners can create workspaces and dashboards and can share their workspace with other analysts under the Personal Org collaboration model.
                                            Because this question expressly includes management of a Personal Org and is framed around a self-service analyst persona, C remains the correct exam-bank answer.
                                            References/Topics: Managing Workspaces and Orgs - > Personal Org - > Tableau Next Creator - > Self- Service Analyst Permissions.


                                            NEW QUESTION # 61
                                            What is a prerequisite for using generative AI to create calculated fields using multi- turn, natural language?

                                            Answer: A

                                            Explanation:
                                            Option A, Draft with Einstein, can generate a calculation from natural language, but the question specifically asks about the multi-turn conversational agent experience, where the agent interacts with the user and refines the requirement. Therefore it is not the best answer. Option B addresses optimization/readiness rather than calculated-field authoring.
                                            References/Topics: Agentic Experiences - > Tableau Agent - > Semantic Modeling/Data Pro - > Conversational Calculated Fields - > Natural-Language Authoring.


                                            NEW QUESTION # 62
                                            ......

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