Salesforce Updated Analytics-Con-301 Exam Questions and Answers by august

Comprehensive and Detailed Explanation From Exact Extract:

Tableau documentation explains:

Tableau Public

Free platform.

Allows public sharing and embedding of fully interactive dashboards.

Ideal for small datasets and infrequent updates.

Does not require user-based licensing.

Embedding is unrestricted because all content is publicly visible.

This perfectly matches the scenario:

✔ Public-facing website

✔ Low cost priority

✔ Small dataset

✔ Manual, infrequent updates

Why the other options are incorrect:

A. Tableau Cloud (per user)

Requires paid licenses.

Does not allow unrestricted public embedding without expensive add-ons.

Designed for secure internal use, not public web-wide embedding.

C. Tableau Embedded Analytics

A paid embedding solution requiring proper licensing.

Designed for large-scale, secure, programmatic embedding — too costly for this use case.

D. Tableau Server (per core)

Requires server infrastructure & licensing.

Far more expensive than Tableau Public.

Thus, Tableau Public is the correct, cost-effective solution.

Tableau Public documentation describing free embedding for public websites.

Comparison guides showing Tableau Cloud/Server require licensing for embedding.

Public vs. Enterprise Tableau deployment best practices.

Comprehensive and Detailed Explanation From Exact Extract:

Tableau documentation states that IN expressions are optimized internally for better query performance than multiple OR statements. They are pushed efficiently to the data source and simplified during query compilation.

The original expression uses two OR conditions, which increases the complexity of row-level evaluation:

[Project] = 'Project 1' OR [Project] = 'Project 2'

Tableau’s performance guidelines recommend replacing multiple OR comparisons with an IN expression whenever possible:

[Project] IN ('Project 1', 'Project 2')

This reduces rendering time by minimizing row evaluation overhead and creating a cleaner, optimized logical condition.

Option D achieves this exactly.

Option A is logically incorrect because a project cannot simultaneously equal both values.

Option B is syntactically incorrect because IN expects a list, not an OR inside the list.

Option C is simply a reformatting of the original OR expression and provides no performance improvement.

Option D is the only valid, optimized solution.

Tableau calculation optimization guidance recommending IN over OR for performance.

Tableau’s query performance notes indicating that OR statements expand logical branches and slow down evaluation.

Best practices for row-level calculations suggesting simplified logical expressions.

Comprehensive and Detailed Explanation From Exact Extract:

To combine Excel and SQL Server data in the same logical data model, Tableau offers two supported capabilities:

Relationships

Recommended modern method for combining tables from multiple sources.

Supports cross-database relationships between Excel and SQL Server.

Maintains separate physical layers but integrates data at query time.

Cross-Database Joins

Allows joining data from different databases in the physical layer.

Fully supported for Excel + MS SQL Server.

Useful when granular row-level merging is needed.

Why the other options are incorrect:

C. Data Blending

Legacy feature, used only when no direct combination is possible.

Tableau recommends relationships instead.

Produces separate queries and may lose row-level detail.

D. Union

Requires tables to have equivalent structure.

Cannot union Excel with SQL Server unless identical column structure exists.

Not appropriate for most mixed-source reporting.

Therefore, the correct techniques are Relationships and Cross-Database Joins.

Tableau data modeling documentation recommending Relationships for multi-source modeling.

Cross-database join support list including Excel + SQL Server.

Comprehensive and Detailed Explanation From Exact Extract:

In Tableau Cloud, database-level RLS can be used only with live connections because:

Tableau Cloud issues SQL queries using the logged-in user's identity.

Extracts break RLS because data is pulled out of the database and stored in Tableau’s hyper file.

To leverage existing RLS rules, Tableau must query the database directly for the user.

Therefore:

Requirement 1:

The Tableau Cloud username (email) must exist in the database

so that the database can enforce RLS using the authenticated identity.

Requirement 2:

Only live data connections support database-native RLS.

Extracts bypass database security and therefore cannot use RLS defined in the database.

Option D is incorrect because RLS is enforced in the database, not configured in Tableau Cloud.

Option B is incorrect because extracts cannot use database RLS.

Thus, correct answers are A and C.

Tableau Cloud live connection security requirements.

Database RLS documentation requiring matching database user identities.

Explanation that extracts bypass database permission systems.