Exam: Analytics-Con-202 Dumps

Analytics-Con-202 Salesforce Certified Tableau Next Consultant Exam

The Analytics-Con-202 Salesforce Certified Tableau Next Consultant Exam is designed for professionals who implement and maintain analytics solutions within the Salesforce ecosystem. The certification focuses on Tableau Next, Data 360, semantic models, Agentic Analytics, dashboards, cross-cloud integration, administration, and workspace management.

Salesforce describes the target candidate as someone with experience across Salesforce, Data 360/Data Cloud architecture, analytics, semantic data models, and Tableau Next implementations.

Analytics-Con-202 Exam Overview

The Salesforce Certified Tableau Next Consultant exam measures practical knowledge required to transform enterprise data into actionable analytics and insights.

Exam Code: Analytics-Con-202
Exam Name: Salesforce Certified Tableau Next Consultant
Vendor: Salesforce
Questions: 60 scored questions + up to 5 unscored questions
Duration: 105 minutes
Passing Score: 65%
Prerequisite: None
Exam Delivery: Online proctored or testing center
Registration Fee: USD $200 plus applicable taxes
Retake Fee: USD $100 plus applicable taxes

Analytics-Con-202 Exam Topics
1. Data Setup — 20%

Candidates should understand:

Semantic model components, design, and application
Semantic data models
Data 360 capabilities
Data integration and data management
Data preparation and modeling
Data architecture
Data processing approaches
Selecting an appropriate data architecture for a business scenario
Preparing data for analytics and Agentic experiences

Data Setup provides the foundation for Tableau Next analytics because semantic models and properly prepared data determine how information can be analyzed and interpreted.

2. Agentic Experiences — 25%

This is the largest Analytics-Con-202 exam domain.

Important areas include:

Generative AI capabilities in Tableau Next
Agentic readiness
Analytics Agent
Exploring data with Analytics Agent
Generating data insights
Proactive data alerts
Notifications
Preparing analytics environments for AI-assisted experiences
Using trusted and well-defined analytical data

Candidates should understand how AI-powered analytics interacts with semantic models and business data.

3. Embedding, Cross-Cloud, & Interoperability — 20%

Key topics include:

Tableau Next integration with Salesforce analytics platforms
Embedding Tableau Next assets
Cross-platform workflows
Tableau Next Apps for Salesforce
Marketplace offerings
Surfacing analytics within user workflows
Developer tools
APIs
Salesforce ecosystem interoperability

This section tests how Tableau Next can operate as part of a broader Salesforce environment rather than as an isolated analytics platform.

4. Basic Setup & Admin — 10%

Study:

Activating Tableau Next features
Managing Tableau Next
User access
Permissions
Appropriate access configuration
Agentic Analytics activation
Administrative configuration
5. Visualizations & Dashboards — 15%

Important areas include:

Tableau Next visualization best practices
Dashboard design
User-friendly analytical experiences
Dashboard actions
Interactive analytics
Designing visualizations for business users
Configuring actions within Tableau Next
6. Managing Workspaces & Orgs — 10%

Candidates should understand:

Personal Org deployment and management
Tableau Next workspaces
Asset management
Asset sharing
Workspace permissions
Tableau Next asset deployment
Managing analytics content across environments

The six domains and their published weightings are reflected in the current Salesforce exam guide.

CertKingdom Analytics-Con-202 preparation materials help Salesforce professionals study for the Salesforce Certified Tableau Next Consultant exam with practice questions, study resources, and test preparation covering Data Setup, Agentic Experiences, Tableau Next integration, administration, dashboards, and workspace management.

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Exam Syllabus & Objectives
Exam Overview
The Salesforce Certified Tableau Next Consultant examination validates your ability to design, implement, and optimize
analytics solutions using Tableau Next. This certification demonstrates proficiency across data architecture, AI-driven
analytics features, cross-platform integration, administrative functions, and dashboard design within the Tableau Next ecosystem.

Data Architecture & Semantic Modeling (20%)
This domain tests your understanding of how to structure and organize data for analytics in Tableau Next. You will need
to grasp the foundational components and design patterns of semantic models, and how they facilitate effective data
representation. Additionally, you should be familiar with Data 360 capabilities that support the full data lifecycle-from
integrating disparate sources through preparation and transformation to creating managed data models. When
presented with real-world business scenarios, you must select the most appropriate data architecture approach and
determine whether certain data processing methods align with project requirements.

Agentic Experiences & Generative AI (25%)
This domain focuses on how artificial intelligence transforms the user experience in Tableau Next. You will demonstrate
knowledge of how generative AI capabilities power the creation of dynamic Tableau Next components and enable more
intelligent analytics workflows. You must understand the prerequisites and readiness criteria for deploying agentic
analytics capabilities in your organization. The Analytics Agent is central to this domain-you should know how it
empowers users to ask natural language questions about data, discover patterns, and generate actionable insights
automatically. Furthermore, you need to understand how the Analytics Agent proactively identifies anomalies and
delivers timely data alerts and notifications to stakeholders.

Cross-Cloud Integration & Developer Tools (20%)
This domain emphasizes how Tableau Next operates as part of the broader Salesforce ecosystem. You must understand
the integration points between Tableau Next and other Salesforce analytics platforms, and how assets and insights flow
seamlessly into user workflows across different applications and touchpoints. You should be familiar with how Tableau
Next Apps for Salesforce and pre-built marketplace solutions reduce implementation time and accelerate business value
realization. Additionally, you need to know what APIs, SDKs, and development tools are available for developers who
build custom extensions or integrate Tableau Next into external systems.
Administration & Feature Activation (10%)
This domain covers the operational and governance aspects of Tableau Next. You must know how to enable and
configure Tableau Next features within your organization, manage user access controls to ensure appropriate capability
exposure, and activate agentic analytics functionality for specific user populations. These administrative skills are
essential for successful deployment and ongoing management of the platform.
Visualization Design & Interactive Components (15%)
This domain tests your ability to create effective, user-centered analytics assets in Tableau Next. You should apply
industry best practices for data visualization and dashboard layout to ensure clarity, usability, and aesthetic appeal. You
must understand how to implement interactive actions-such as filtering, drilling, and navigation-that allow users to
explore data intuitively and derive deeper insights from visual representations.
Workspace Management & Deployment (10%)
This domain addresses how to organize, govern, and deliver Tableau Next assets across your organization. You should
understand how to deploy and maintain a Personal Org environment, manage permissions and sharing policies to
control asset access, and deploy Tableau Next solutions in alignment with organizational standards. These capabilities
ensure that analytics assets reach the right users in a secure and scalable manner.

QUESTION 1
A Salesforce administrator is designing a data architecture for a financial services company that needs to
analyze sales pipeline data alongside account health metrics from multiple Salesforce orgs. The company
wants to surface insights directly within the Salesforce CRM interface and enable business users to ask
natural language questions about their data without writing formulas or building complex visualizations.
Which combination of Tableau Next components and Data 360 features should the administrator recommend
to meet these requirements?

A. Create a semantic model in Data 360 that unions data from multiple Salesforce orgs, then embed
Tableau dashboards in Salesforce using the Tableau Next App for Salesforce, and enable the Analytics
Agent to support natural language queries
B. Build separate Tableau Server workbooks for each org, configure row-level security filters, and deploy
using Tableau Public for cross-org visibility
C. Use only Salesforce Reports and Dashboards with Einstein Analytics for data integration, then enable
Slack notifications for alerts
D. Implement Tableau Desktop with multi-dimensional cubes connected to Salesforce APIs, then manually
refresh data daily using Tableau Prep Builder
E. Deploy a Personal Org in Tableau Next, disable the Analytics Agent to maintain data security, and
configure email-only sharing for all assets

Answer: A

Explanation:
The correct answer integrates three key Tableau Next capabilities: semantic models in Data 360 (for unified
data management across multiple sources), the Tableau Next App for Salesforce (for embedding and
surfacing assets within CRM workflows), and the Analytics Agent (for enabling natural language exploration
without requiring technical skills).
The other options miss critical requirements: Option B uses outdated Tableau Server architecture and Tableau
Public (not appropriate for sensitive financial data). Option C relies solely on Einstein Analytics without the
semantic modeling and agentic capabilities that Tableau Next provides. Option D uses Tableau Desktop and
manual processes, which don't scale to multi-org scenarios. Option E incorrectly disables the Analytics Agent,
which is essential for natural language capabilities, and Personal Orgs are not designed for enterprise cross-org scenarios.

QUESTION 2
A Tableau Next consultant is implementing a Personal Org for a regional sales director who needs to monitor
pipeline velocity and forecast accuracy. Before activation, the consultant must assess whether the
environment meets Agentic Analytics readiness requirements. The organization uses Salesforce Core with
custom objects, has enabled Data 360, and wants to allow the Analytics Agent to automatically generate
proactive alerts when forecast accuracy drops below a defined threshold.
What are the key prerequisites the consultant must verify to enable Agentic Analytics in this scenario?
(Select all that apply)

A. The semantic model must be properly configured in Data 360 with appropriate data lineage and
metadata annotations so the Analytics Agent can understand and contextualize the data
B. The user must have the Analytics Agent Administrator or Analytics Agent Editor role assigned in
Tableau Next to receive and configure proactive alerts
C. Salesforce Einstein must be enabled at the org level with minimum 50 additional licenses beyond the base org
D. All data must be moved from custom Salesforce objects to the Salesforce data cloud before the
Analytics Agent can access it
E. The Personal Org must be configured with explicit permission settings that grant the Analytics Agent
read access to the semantic model

Answer: A, B, E

Explanation:
The three correct answers reflect actual Agentic Analytics prerequisites: (1) semantic models must include
proper metadata and lineage so the agent can interpret data context and relationships, (2) users need
appropriate Tableau Next roles to interact with and configure agent capabilities, and (3) permission settings
must explicitly allow the agent to read from the semantic model.
The incorrect options contain common misconceptions: Option C assumes Einstein must be separately licensed
and configured, which is not a prerequisite for Agentic Analytics in Tableau Next-the agentic capabilities are
built into Tableau Next itself. Option D is false because custom Salesforce objects can be included in Data 360
semantic models directly; migration to the data cloud is not required for the agent to access them. The
Analytics Agent can work with custom objects as long as they are properly modeled in the semantic layer.

QUESTION 3
A Tableau Next consultant is designing a dashboard that will be embedded in Salesforce for account
managers to view customer health scores and service metrics. The dashboard must allow users to drill into
account-specific data when they click on a customer name, and it should automatically filter subsequent
queries based on the account context from the Salesforce record currently being viewed.
Which approach should the consultant use to configure this functionality?

A. Configure a dashboard action that uses Salesforce field mapping to pass the account ID from the
Salesforce context into a semantic model filter parameter, ensuring the embedded dashboard respects
the user's row-level security in the semantic model
B. Implement a Tableau Server bookmark that users manually select before viewing the dashboard, then
apply static filters based on user groups
C. Build the dashboard in Tableau Desktop with hardcoded account IDs, then publish directly to Salesforce
using the Tableau Public API
D. Create a separate dashboard for each account and distribute them via email links to account managers
each week
E. Use Salesforce flow automation to replace all dashboard filters with Einstein Analytics lenses instead of
Tableau visualizations

Answer: A

Explanation:
The correct answer describes the proper Tableau Next embedding pattern: dashboard actions with
Salesforce field mapping enable dynamic context-aware filtering. This approach passes the account ID from
the Salesforce page context into a semantic model filter parameter, ensuring the dashboard automatically
displays only relevant data and respects row-level security policies defined in the semantic layer.
Option B uses outdated Tableau Server bookmarks, which don't leverage modern Salesforce context passing.
Option C hardcodes data and references Tableau Public, neither of which is appropriate for embedded
enterprise scenarios. Option D is inefficient and doesn't provide real-time context awareness. Option E
incorrectly suggests replacing Tableau visualizations with Einstein Analytics-Tableau Next and Einstein
Analytics are complementary tools, not replacements for each other, and the scenario specifically requires
Tableau dashboard functionality.

QUESTION 4
A Tableau Next consultant is advising a retail company on deploying Tableau Next assets across their
Personal Org. The company has two regional teams (North and South), each with different data access
requirements based on their territories. The consultant recommends using workspace-level sharing and
permissions to manage access. However, the regional leaders also want certain insights to be discoverable
and automatically available to new employees in their region without manual provisioning.
What combination of workspace and organizational management practices should the consultant
recommend?

A. Create separate workspaces for each region, assign team groups (not individuals) to each workspace,
configure workspace permissions to grant view and edit access by role, and use group-based sharing
policies to automatically include new team members as they are added to regional groups in Salesforce
B. Place all assets in a single global workspace with row-level security filters in the semantic model, then
manually add each new employee to Tableau individually
C. Use only Personal Orgs for each regional team without creating shared workspaces, then distribute
asset links via email distribution lists
D. Configure all sharing through Salesforce Slack integration and disable Tableau workspace permissions entirely
E. Create one workspace per asset instead of one per region, and assign read-only access to all users
regardless of territory

Answer: A

Explanation:
The correct answer follows Tableau Next best practices for scalable access management: separate workspaces
align with organizational structure (regions), group-based assignment (not individual assignments) enables
automatic provisioning, and role-based workspace permissions provide scalable governance. When new
employees are added to regional groups in Salesforce, they automatically inherit workspace access without
manual intervention.
Option B centralizes assets without organizational clarity and requires manual provisioning, defeating the goal
of automatic access for new hires. Option C misuses Personal Orgs-they are for individual analysis, not team
collaboration, and email distribution is not a secure or auditable access control method. Option D incorrectly
suggests disabling workspace permissions, which are fundamental to security and governance. Option E
creates an unscalable asset-per-workspace structure and unnecessarily grants broad read-only access without
respecting territorial boundaries.

QUESTION 5
A Salesforce organization is preparing to activate Tableau Next for their marketing team. The administrator
has already configured the necessary licensing and enabled Data 360. However, before enabling Agentic
Analytics, the admin needs to understand what activation steps are required to make the Analytics Agent
available to end users.
What is the correct sequence and scope of Agentic Analytics activation?

A. Enable Agentic Analytics at the org level in Tableau Next settings, assign the Analytics Agent User or
Analytics Agent Administrator role to specific users, ensure those users have access to semantic
models through workspace-level permissions, and verify that the semantic models include proper
metadata configuration
B. Automatically activate the Analytics Agent for all users once Data 360 is enabled, with no additional
configuration needed
C. Enable Agentic Analytics only for users with Tableau Creator licenses, then use Salesforce permission
sets to restrict access to specific dashboards
D. Activate the Analytics Agent through Einstein Analytics settings in Setup, then grant all marketing users
admin rights in Tableau Next
E. Purchase separate Agentic Analytics licenses beyond standard Tableau Next licensing, then deploy
through a Salesforce Flow automation

Answer: A

Explanation:
The correct answer reflects the actual Agentic Analytics activation process: (1) org-level enablement in Tableau
Next settings, (2) role assignment to control which users can interact with the agent, (3) workspace and
semantic model permissions to determine what data the agent can access, and (4) metadata in the semantic
layer to enable the agent to understand and reason about data.
Option B incorrectly assumes auto-activation; Agentic Analytics requires explicit enablement and role
assignment. Option C incorrectly ties activation to license type-Agentic Analytics is available across multiple
license tiers, not restricted to Creators only, and dashboard restrictions don't govern agent activation. Option D
conflates Agentic Analytics with Einstein Analytics, which are separate capabilities in different products. Option
E misrepresents licensing-Agentic Analytics is included in Tableau Next licensing, not sold separately, and
should not be configured through Salesforce Flow automation.

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Student Reviews

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Salesforce's official guide recommends hands-on experience, Trailhead training and self-study for this certification.

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FAQ Section

15 Frequently Asked Questions (FAQs)


1. What is Analytics-Con-202?

Analytics-Con-202 is the exam code for the Salesforce Certified Tableau Next Consultant certification.

2. What does the Salesforce Tableau Next Consultant certification cover?

The exam covers Data Setup, Agentic Experiences, Embedding/Cross-Cloud/Interoperability, Basic Setup & Admin, Visualizations & Dashboards, and Managing Workspaces & Orgs.

3. How many questions are on Analytics-Con-202?

The current Salesforce exam guide specifies 60 scored multiple-choice questions plus up to 5 unscored questions.

4. How long is the Analytics-Con-202 exam?

Candidates have 105 minutes to complete the exam.

5. What is the passing score for Analytics-Con-202?

The published passing score is 65%.

6. Is there a prerequisite for Analytics-Con-202?

Salesforce currently lists no prerequisite for the certification.

7. Which Analytics-Con-202 domain has the highest weighting?

Agentic Experiences accounts for 25% of the exam, followed by Data Setup at 20% and Embedding, Cross-Cloud & Interoperability at 20%.

8. What should I study about Data 360?

Focus on Data 360 data integration, management, preparation, modeling, semantic models, and selecting suitable data architecture or processing approaches.

9. What is Agentic Analytics?

For this certification, candidates need to understand how generative AI and the Analytics Agent support data exploration, insight generation, alerts, and notifications within Tableau Next.

10. What are Tableau Next semantic models?

Semantic models provide the analytical structure used to organize and interpret business data, including concepts needed for consistent analytics and AI-assisted experiences.

11. Does Analytics-Con-202 cover Salesforce integration?

Yes. The exam includes Tableau Next integration with Salesforce analytics platforms, cross-platform workflows, Tableau Next Apps for Salesforce, Marketplace offerings, and developer tools/APIs.

12. Are Tableau Next dashboards included in the exam?

Yes. Visualizations & Dashboards represents 15% of the exam and includes visualization best practices and dashboard actions.

13. Does the exam cover workspace management?

Yes. Managing Workspaces & Orgs represents 10% and includes Personal Orgs, asset management/sharing, and asset deployment.

14. What Salesforce resources can I use to prepare?

Salesforce recommends a combination of hands-on experience, training, Trailhead, and self-study. The official guide specifically points candidates toward the Prepare for Your Salesforce Tableau Next Consultant Certification Trailhead path.

15. How should I prepare for Analytics-Con-202?

A practical preparation approach is to study the official exam domains, build hands-on familiarity with Tableau Next and Data 360, review Agentic Analytics concepts, and use practice questions to identify weak areas before the exam. Salesforce recommends combining hands-on experience with training and self-study.