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Salesforce Analytics-Con-301 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • Business Consulting: For Tableau Consultants, this section involves designing and troubleshooting calculations and workbooks to meet advanced analytical use cases. It covers selecting appropriate chart types, applying Tableau’s order of operations in calculations, building interactivity into dashboards, and optimizing workbook performance by resolving resource-intensive queries and other design-related issues.
Topic 3
  • 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 4
  • 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.
Topic 5
  • 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.

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Salesforce Certified Tableau Consultant Sample Questions (Q42-Q47):

NEW QUESTION # 42
A consultant used Tableau Data Catalog to determine which workbooks will be affected by a field change.
Catalog shows:
* Published Data Source # 7 connected workbooks
* Field search (Lineage tab) # 6 impacted workbooks
The client asks: Why 7 connected, but only 6 impacted?

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
Key Tableau Catalog behaviors:
* Connected workbooks = any workbook linked to the published data source.
* Impacted workbooks = only workbooks that use the specific field.
* If a workbook connects to the data source but never uses the field, it appears as "connected" but not impacted.
This explains EXACTLY why:
* 7 workbooks are connected
* Only 6 use the changed field
* Therefore only 6 are impacted
This matches Option C.
Why the other options are incorrect:
A). Field used twice
Still counts as one workbook - does not explain discrepancy.
B). Permission issue
If permissions blocked visibility, the data source would not list 7 connections.
D). Custom SQL use
Catalog can still detect field usage through metadata lineage; Custom SQL does NOT hide workbook dependency.
Thus, only Option C logically explains the scenario.
* Data Catalog lineage rules: "Connected vs. Impacted" distinction.
* Field-level impact analysis documentation.
* Workbook dependency logic within Tableau Catalog.


NEW QUESTION # 43
A client wants to see the average number of orders per customer per month, broken down by region. The client has created the following calculated field:
Orders per Customer: {FIXED [Customer ID]: COUNTD([Order ID])}
The client then creates a line chart that plots AVG(Orders per Customer) over MONTH(Order Date) by Region. The numbers shown by this chart are far higher than the customer expects.
The client asks a consultant to rewrite the calculation so the result meets their expectation.
Which calculation should the consultant use?

Answer: A

Explanation:
The calculation {FIXED [Customer ID], [Region]: COUNTD([Order ID])} is the correct one to use for this scenario. This Level of Detail (LOD) expression will calculate the distinct count of orders for each customer within each region, which is then averaged per month. This approach ensures that the average number of orders per customer is accurately calculated for each region and then broken down by month, aligning with the client's expectations.
References: The LOD expressions in Tableau allow for precise control over the level of detail at which calculations are performed, which is essential for accurate data analysis. The use of {FIXED} expressions to specify the granularity of the calculation is a common practice and is well-documented in Tableau's official resources12.
The initial calculation provided by the client likely overestimates the average number of orders per customer per month by region due to improper granularity control. The revised calculation must take into account both the customer and the region to correctly aggregate the data:
FIXED Level of Detail Expression: This calculation uses a FIXED expression to count distinct order IDs for each customer within each region. This ensures that the count of orders is correctly grouped by both customer ID and region, addressing potential duplication or misaggregation issues.
Accurate Aggregation: By specifying both [Customer ID] and [Region] in the FIXED expression, the calculation prevents the overcounting of orders that may appear if only customer ID was considered, especially when a customer could be ordering from multiple regions.
References:
Level of Detail Expressions in Tableau: These expressions allow you to specify the level of granularity you need for your calculations, independent of the visualization's level of detail, thus offering precise control over data aggregation.


NEW QUESTION # 44
In what way does View Acceleration improve performance?

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
View Acceleration is a Tableau Server and Tableau Cloud feature that speeds up slow-loading views by precomputing their queries in the background.
According to Tableau's server and cloud performance documentation:
* When View Acceleration is enabled for a view, Tableau runs the queries behind that view on a background process and stores the results in memory.
* When an end user later opens the view, Tableau can serve the precomputed results immediately, rather than running the potentially long-running queries at that moment.
* This improves initial load time significantly for views that are slow because of heavy queries.
It does not only work with extract-based data sources (it can also help with many live connections), so option A is too limited.
It does not change the client-side rendering engine, so option C is incorrect.
It is not specific to transient functions but to any view where the query is expensive, so option D is not accurate.
Therefore, the correct description is that View Acceleration precompiles and fetches workbook data in a background process, which matches option B.
* Tableau Server and Tableau Cloud help describing View Acceleration as precomputing and caching view results using background processes.
* Performance tuning guidance recommending View Acceleration for views with slow query execution.


NEW QUESTION # 45
A client has a published dashboard. They change the dashboard and then republish it. Now, users report that their web browser bookmarks to the dashboard are broken.
What are two possible causes for this issue? Choose two.

Answer: C,D

Explanation:
When a client republishes a dashboard after making changes and users report broken bookmarks, the likely causes include:
The dashboard was published to a different project: Changing the project location alters the URL path, causing bookmarks to point to a now non-existent dashboard location.
The dashboard was published with a new name: Altering the dashboard's name changes its URL, resulting in broken bookmarks as the previous URL no longer leads to the intended dashboard.


NEW QUESTION # 46
For a new report, a consultant needs to build a data model with three different tables, including two that contain hierarchies of locations and products. The third table contains detailed warehousing data from all locations across six countries. The consultant uses Tableau Cloud and the size of the third table excludes using an extract.
What is the most performant approach to model the data for a live connection?

Answer: A

Explanation:
For a performant live connection in Tableau Cloud, especially when dealing with large datasets that preclude the use of extracts, relating the tables in Tableau Desktop is the recommended approach. This method allows for flexibility in how the data is queried and can improve performance by leveraging Tableau's relationships feature, which optimizes queries for the underlying database.
References: The best practices for live connections in Tableau Cloud suggest using relationships to manage complex data models efficiently1. Additionally, Tableau's documentation on connecting data sources recommends using relationships for better performance with live connections2.


NEW QUESTION # 47
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