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Salesforce Analytics-Con-301 Exam Syllabus Topics:

TopicDetails
Topic 1
  • IT Management: This domain measures skills related to managing Tableau environments. It includes planning server upgrades, recommending deployment solutions (on-premise or cloud), and ensuring alignment between technical and business requirements for analytics infrastructure. It also involves troubleshooting and optimizing system performance relevant to Tableau Server and Cloud deployments.
Topic 2
  • Data Management: This part focuses on establishing governance and support for published content. Tableau Consultants are expected to manage data security, publish and maintain data sources and workbooks, and oversee content access. It includes applying governance best practices, using metadata APIs, and supporting administration functions to maintain data integrity and accessibility.
Topic 3
  • Data Visualization: This section evaluates the Tableau Consultant’s ability to design effective visual analytics solutions. It involves creating dashboards and visual reports that enhance user understanding, employing techniques like dynamic actions and advanced chart types, and ensuring performance optimization for an interactive user experience.
Topic 4
  • Data Analysis: This domain targets Tableau Consultants to plan and prepare data connections effectively. It includes recommending data transformation strategies, designing row-level security (RLS) data structures, and implementing advanced data connections such as Web Data Connectors and Tableau Bridge. Skills in specifying granularity and aggregation strategies for data sources across Tableau products are emphasized.
Topic 5
  • Business Analysis: This section of the exam measures skills of Tableau Consultants focusing on evaluating the current state of analytics within an organization. It covers mapping business needs to Tableau capabilities, translating analytical requirements to best practices in Tableau, and recommending appropriate deployment options like Tableau Server or Tableau Cloud. It also includes evaluating existing data structures for supporting business needs and identifying performance risks and opportunities.

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Salesforce Certified Tableau Consultant Sample Questions (Q15-Q20):

NEW QUESTION # 15
An executive-level workbook leverages 37 of the 103 fields included in a data source. Performance for the workbook is noticeably slower than other workbooks on the same Tableau Server.
What should the consultant do to improve performance of this workbook while following best practice?

Answer: B

Explanation:
To improve the performance of a Tableau workbook, it is best practice to streamline the data being used. This can be achieved by using filters to limit the data to only what is necessary for analysis, hiding fields that are not being used to reduce the complexity of the data model, and aggregating values to simplify the data and reduce the number of rows that need to be processed. These steps can help reduce the load on the server and improve the speed of the workbook.
References: The best practices for optimizing workbook performance in Tableau are well-documented in Tableau's official resources, including the Tableau Help Guide and the Designing Efficient Workbooks whitepaper, which provide detailed recommendations on how to streamline workbooks for better performance12.


NEW QUESTION # 16
A database contains two related tables at different levels of granularity. The client wants to make all data available in Tableau Prep at the original level of granularity.
Which two solutions in Tableau meet the client's requirements? Choose two.

Answer: B,D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The key requirement is:
# Data must remain at the original grain in Tableau Prep
# Tables are at different granularities
Tableau Prep does NOT support relationships, and automatically joins tables, which changes granularity (by duplicating or aggregating records).
Therefore, relationships (Option B) cannot preserve grain for Prep.
Also:
* A physical join (Option D) changes the grain by combining rows, often multiplying results when grain differs.
Only two options preserve the original granularity:
Option A - Two Separate Published Data Sources
Each data source represents one table.
In Tableau Prep, the user can choose:
* Use tables separately
* Join or clean them intentionally
* Keep each table at its own grain
This keeps all data at its native level.
Option C - Virtual Connection
A Virtual Connection:
* Publishes entire tables from the database
* Maintains each table independently at its native granularity
* Makes all tables available to Tableau Prep without altering grain
* Is specifically designed for governed, reusable multi-table access
Thus, it satisfies the requirement exactly.
Why the others are incorrect:
B - Relationship
Relationships only exist in Tableau Desktop logical layer, NOT in Tableau Prep.
Prep flattens the data # grain is lost.
D - Physical join
Always modifies granularity when tables differ, often causing row multiplication.
* Tableau Prep does not support logical relationships; only physical joins.
* Virtual Connections preserve original tables and governance.
* Published Data Sources can be separated to maintain original grain.


NEW QUESTION # 17
A client has a published data source in Tableau Server and they want to revert to the previous version of the data source. The solution must minimize the impact on users.
What should the consultant do to accomplish this task?

Answer: C

Explanation:
To minimize the impact on users when reverting to a previous version of a published data source in Tableau Server, the consultant should use the built-in revision history feature. By selecting a previous version from the revision history and clicking 'Restore', the data source will revert to that version without the need for a full server backup restoration or manual recreation of the data source. This process is quick and has the least amount of disruption to users.
References: The functionality and process for reverting to a previous version of a data source are outlined in Tableau's official documentation on working with content revisions1. This feature is part of Tableau Server's capabilities to manage and maintain data sources effectively21.


NEW QUESTION # 18
A consultant updates an IF-THEN calculation to use a newly created calculated field "Last Name" (parsed from "Full Name"). After the change, performance becomes noticeably worse.
Which two options should the consultant use to improve dashboard performance without altering functionality? Choose two.

Answer: A,D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The performance degradation originates from string parsing inside Tableau ("last word of Full Name") and then feeding that calculated field into another row-level IF-THEN calculation.
This creates:
* Nested calculations
* High per-row evaluation load
* Slow extract query performance or slow live query generation
Tableau documentation recommends two best-practice approaches:
Solution 1: Precompute the "Last Name" field upstream (Option C)
When the parsing is performed in:
* The database
* ETL/ELT pipelines
* Tableau Prep
then Tableau Desktop receives a clean field with no runtime computation needed.
This significantly reduces row-level calculation burden.
Solution 2: Replace Quick Filters with Action Filters (Option A)
Quick filters are expensive because Tableau:
* Runs additional queries to populate filter controls
* Re-queries every time the filter changes
Action Filters run directly from the visualization and are far more performant.
This improves the overall dashboard performance without changing logic.
Why the other options are incorrect:
B). Calculate "Last Name" inside the IF THEN calculation
This makes the expression even more complex - worse performance.
D). Change to a CASE statement
CASE does not improve performance when the heavy part of the logic is the string parsing, not the IF-THEN structure.
Thus, A and C are the correct performance-improving choices.
* Performance guidance recommending upstream computation of string fields
* Filter optimization best practices encouraging Action Filters over Quick Filters
* Extract runtime cost reduction strategies


NEW QUESTION # 19
A transport and delivery company uses a command center dashboard in its logistics and distribution hubs. The dashboard is displayed on screens to show fleet movements, delivery status, and warehouse operations. The company needs the dashboard to provide up-to-date information without human intervention. The company's environment cannot access the internet, and the data source is configured to maintain a real-time connection.
How should the company meet this requirement?

Answer: C

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
Key details from the scenario:
* The dashboard is on a command center screen.
* The environment cannot access the internet.
* The data source is real-time (live).
* The dashboard must keep itself refreshed automatically.
* No human interaction should be required.
From Tableau's documentation:
# Dashboard Extension API
Tableau's Extension API allows developers to create custom extensions that can automate refreshing a live dashboard at intervals.
The extension is hosted on the company's internal web server, which solves the "no internet access" limitation.
This is the only method in the listed options that:
* Works offline
* Can auto-refresh the dashboard
* Supports a "screen-based" live monitoring use case
* Uses the existing live connection (no need for extracts)
Thus, A is correct.
Why the other options are wrong:
# B. Schedule a Prep Flow
Prep flows do not refresh dashboards.
They only refresh prepared data sources.
The dashboard still won't auto-update unless reopened.
# C. Download an extension from Tableau Exchange
Tableau Exchange requires internet access, which the company does not have.
Also, "sandboxed extensions" cannot refresh the dashboard at timed intervals.
# D. Use extracts and scheduled extract refresh
Extracts require:
* A Tableau Server / Cloud schedule
* Internet access for Cloud
* And extracts are not real-timeThis contradicts the requirement for real-time data and an offline environment.


NEW QUESTION # 20
......

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