Valid TCC-C01 Mock Exam & TCC-C01 Regualer Update

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Tableau TCC-C01 Exam Syllabus Topics:

Topic	Details
Topic 1	Plan and Prepare Data Connections: This section focuses on planning data transformation and preparing connections, targeting Tableau-certified consultants. Candidates will recommend data storage methods, design row-level security structures, and troubleshoot complex data connection issues.
Topic 2	Design and Troubleshoot Calculations and Workbooks: This domain evaluates the ability to design advanced analytics and troubleshoot workbooks. Candidates will implement calculations, optimize performance, and plan interactivity for dashboards while resolving performance issues.
Topic 3	Establish Governance and Support Published Content: This section measures the skills of Tableau-certified consultants related to governance strategies within Tableau environments. Candidates will map governance requirements, recommend content access strategies, design administrative views, and identify external errors affecting performance.
Topic 4	Evaluate Current State: This domain measures the skills of Tableau-certified consultants in assessing the current analytics landscape. Candidates will evaluate existing reports and data structures to ensure alignment with business needs and recommend appropriate Tableau deployment options.

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Tableau Certified Consultant Sample Questions (Q18-Q23):

NEW QUESTION # 18
A client wants to flag orders that have sales higher than the regional average.
Which calculated field will produce the required result?

A. { FIXED [Order ID] : SUM([Sales]) }
>
{ FIXED [Region] : SUM([Sales]) }
B. [Sales]
>
{ FIXED [Order ID] : SUM([Sales]) }
C. { FIXED [Order ID] : SUM([Sales]) }
>
{ FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }
D. { FIXED [Order ID] : SUM([Sales]) }
>
{ INCLUDE [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }

Answer: C

Explanation:
To flag orders with sales higher than the regional average, the correct calculated field would compare the sum of sales for each order against the average sales of all orders within the same region:
* Correct Formula:{ FIXED [Order ID] : SUM([Sales]) } > { FIXED [Region] : AVG({ FIXED
[Order ID] : SUM([Sales]) }) }
* This calculation uses a Level of Detail (LOD) expression:
* The left part of the formula{ FIXED [Order ID] : SUM([Sales]) }calculates the total sales for each individual order.
* The right part{ FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }calculates the average sales per order within each region.
* The>operator is used to compare these two values to determine if the sales for each order exceed the regional average.
ReferencesThis formula utilizes Tableau's LOD expressions to perform complex comparisons across different dimensions of the data, as explained in Tableau's official training materials on LOD calculations.

NEW QUESTION # 19
A client uses Tableau Data Management and notices that when they view a data source, they sometimes see a different count of workbooks in the Connected Workbooks tab compared to the lineage count in Tableau Catalog.
What is the cause of this discrepancy?

A. Some Creators have connected to the data source in Tableau Desktop but have not yet published a workbook.
B. Some workbooks have not been viewed by enough users yet.
C. Some workbooks have been connected to the data source, but do not use any fields from it.
D. Some of the workbooks connected to the data source are not visible to the user due to permissions.

Answer: D

Explanation:
The discrepancy between the count of workbooks in the Connected Workbooks tab and the lineage count in Tableau Catalog can occur because of user permissions. In Tableau Data Management, the visibility of connected workbooks is subject to the permissions set by administrators. If a user does not have permission to view certain workbooks, they will not see them listed in the Connected Workbooks tab, even though these workbooks are part of the data source's lineage and are counted in Tableau Catalog.
References:This explanation is based on the functionality of Tableau Data Management and Tableau Catalog, which includes managing user permissions and access to workbooks.The information is supported by Tableau's official documentation on data management and security practices1.

NEW QUESTION # 20
A client wants to count all the distinct orders placed in 2010. They have written the following calculation, but the result is incorrect.
IF YEAR([Date])=2010 THEN COUNTD ([OrderID]) END
Which calculation will produce the correct result?

A. COUNT(IF YEAR([Date])=2010 THEN [OrderID] END)
B. COUNTD(IF YEAR([Date])=2010 THEN [OrderID] END)
C. IF MIN(YEAR([Date]))=2010 THEN WINDOW_COUNTD([OrderID]) END
D. IF YEAR([Date])=2010 THEN {COUNTD ([OrderID])} END

Answer: B

Explanation:
The correct calculation to count all distinct orders placed in 2010 involves placing the conditional inside the aggregation function, not the other way around. Here's how to correct the client's calculation:
* Original Calculation Issue: The client's original calculation attempts to apply theCOUNTDfunction within anIFstatement, which does not work as expected because theCOUNTDfunction cannot conditionally count within the scope of theIFstatement.
* Correct Calculation:COUNTD(IF YEAR([Date]) = 2010 THEN [OrderID] END). This calculation checks each order date; if the year is 2010, it returns theOrderID. TheCOUNTDfunction then counts all uniqueOrderIDs that meet this condition.
* Why It Works: This method ensures that each order is first checked for the year condition before being counted, effectively filtering and counting in one step. It efficiently processes the data by focusing the distinct count operation only on relevant records.
ReferencesThis approach is consistent with Tableau's guidance on using conditional logic inside aggregation functions for accurate and efficient data calculations, as detailed in the Tableau User Guide under
"Aggregations and Calculations".

NEW QUESTION # 21
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?

A. Relating the tables in Tableau Desktop
B. Joining the tables in Tableau Prep
C. Joining the tables in Tableau Desktop
D. Blending the first two tables with the third

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 # 22
A client needs to design row-level security (RLS) measures for their reports. The client does not currently have Tableau Data Management Add-on, and it may be an option in the future.
What should the consultant recommend as the safest and easiest way to manage for the long term?

A. Create User filters based on data policies and apply them to views using set filters and option Server/Create User Filter.
B. Create User filters for each report using a table joined to its data source and using the option Apply to All Sheet Using the Data Source.
C. Create User filters in each view of each report using set filters and option Server/Create User Filter.
D. Create User filters based on data policies and apply them to a published data source.

Answer: D

Explanation:
For implementing row-level security (RLS) without the Tableau Data Management Add-on, the best approach is to integrate user filters into the published data source:
* Creating User Filters on Published Data Source: This method involves defining user filters that apply directly to the data source before it is published to the Tableau Server. This ensures that any workbook or view leveraging this data source inherently respects the row-level security settings.
* To implement this, create a calculated field in Tableau that defines the security logic, typically using a formula that references user functions (likeUSERNAME()orISMEMBEROF()). Drag this field to the Filters shelf and configure it to match the security rules (who can see what data).
* Once configured, publish the data source to Tableau Server with these filters in place. This approach centralizes security management, making it easier to maintain and update security policies as they are applied universally to all workbooks using this data source.
This strategy is safe as it reduces the risk of accidental data exposure through individual workbook misconfiguration and simplifies long-term maintenance of security policies.
ReferencesThis method follows Tableau's best practices for implementing row-level security as detailed in Tableau's security management resources. It ensures robust, maintainable security measures that scale with organizational needs without requiring additional add-ons.

NEW QUESTION # 23
......

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Valid TCC-C01 Mock Exam & TCC-C01 Regualer Update

Tableau TCC-C01 Exam Syllabus Topics:

TCC-C01 Regualer Update - Valid Exam TCC-C01 Vce Free

Tableau Certified Consultant Sample Questions (Q18-Q23):

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