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copyright Certified Tableau Consultant Sample Questions (Q37-Q42):
NEW QUESTION # 37
A Tableau Server customer is interested in measuring content and platform usage. Which two features should the consultant use? Choose two.
- A. Admin Insights page
- B. Tableau Server repository
- C. Tableau Pulse
- D. Server Status page
Answer: A,B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
Two Tableau Server features provide usage and adoption insights:
Tableau Server Repository
* Stores all metadata about:
* Workbooks
* Data sources
* User activity
* View traffic
* Can be queried directly for content usage and platform metrics.
Admin Insights Page
* Built-in dashboards showing:
* User activity
* Content usage
* Data source usage
* Performance metrics
* Designed specifically for monitoring platform adoption.
These two together give complete content and usage visibility.
Why A and D are incorrect:
A). Tableau Pulse
* Available only in Tableau Cloud, not Tableau Server.
* Focuses on personalized metric insights, not platform reporting.
D). Server Status Page
* Shows node health and process status, not content usage or adoption analytics.
Thus, correct answers are B and C.
* Tableau Server auditing and usage documentation describing repository tables.
* Admin Insights documentation describing built-in content and user monitoring.
NEW QUESTION # 38
SIMULATION
Refer to the exhibit.
From the desktop, open the NYC
Property Transactions workbook.
You need to record the performance of
the Property Transactions dashboard in
the NYC Property Transactions.twbx
workbook. Ensure that you start the
recording as soon as you open the
workbook. Open the Property
Transactions dashboard, reset the filters
on the dashboard to show all values, and
stop the recording. Save the recording in
C:CCData.
Create a new worksheet in the
performance recording. In the worksheet,
create a bar chart to show the elapsed
time of each command name by
worksheet, to show how each sheet in
the Property Transactions dashboard
contributes to the overall load time.
From the File menu in Tableau Desktop,
click Save. Save the performance
recording in C:CCData.
Answer:
Explanation:
See the complete Steps below in Explanation
Explanation:
To record the performance of the Property Transactions dashboard in the NYC Property Transactions.twbx workbook and analyze it using a bar chart, follow these detailed steps:
Open the NYC Property Transactions Workbook:
From the desktop, double-click the NYC Property Transactions.twbx workbook to open it in Tableau Desktop.
Start Performance Recording:
Before doing anything else, navigate to the 'Help' menu in Tableau Desktop.
Select 'Settings and Performance', then choose 'Start Performance Recording'.
Open the Property Transactions Dashboard and Reset Filters:
Navigate to the Property Transactions dashboard within the workbook.
Reset all filters to show all values. This usually involves selecting the dropdown on each filter and choosing 'All' or using a 'Reset' button if available.
Stop the Performance Recording:
Go back to the 'Help' menu.
Choose 'Settings and Performance', then select 'Stop Performance Recording'.
Tableau will automatically open a new tab displaying the performance recording results.
Save the Performance Recording:
In the performance recording results tab, go to the 'File' menu.
Click 'Save As' and navigate to the C:CCData directory.
Save the file, ensuring it is stored in the desired location.
Create a New Worksheet for Performance Analysis:
Return to the NYC Property Transactions workbook and create a new worksheet by clicking on the 'New Worksheet' icon.
Drag the 'Command Name' field to the Columns shelf.
Drag the 'Elapsed Time' field to the Rows shelf.
Ensure that the 'Worksheet' field is also included in the analysis to break down the time by individual sheets within the dashboard.
Choose 'Bar Chart' from the 'Show Me' options to display the data as a bar chart.
Customize and Finalize the Bar Chart:
Adjust the axes and labels to clearly display the information.
Format the chart to enhance readability, applying color coding or sorting as needed to emphasize sheets with longer load times.
Save Your Work:
Once the new worksheet and the performance recording are complete, ensure all work is saved.
Navigate to the 'File' menu and click 'Save', confirming that changes are stored in the workbook.
References:
Tableau Help Documentation: Provides guidance on how to start and stop performance recordings and analyze them.
Tableau Visualization Techniques: Offers tips on creating effective bar charts for performance data.
By following these steps, you have successfully recorded and analyzed the performance of the Property Transactions dashboard, providing valuable insights into how each component of the dashboard contributes to the overall load time. This analysis is crucial for optimizing dashboard performance and ensuring efficient data visualization.
NEW QUESTION # 39
A stakeholder has multiple files saved (CSV/Tables) in a single location. A few files from the location are required for analysis. Data transformation (calculations) is required for the files before designing the visuals. The files have the following attributes:
. All files have the same schema.
. Multiple files have something in common among their file names.
. Each file has a unique key column.
Which data transformation strategy should the consultant use to deliver the best optimized result?
- A. Use join option to combine/merge all the files together before doing the data transformation (calculations).
- B. Apply the data transformation (calculations) in each require file and do the wildcard union to combine/merge before designing the visuals.
- C. Use wildcard Union option to combine/merge all the files together before doing the data transformation (calculations).
- D. Apply the data transformation (calculations) in each require file and do the join to combine/merge before designing the visuals.
Answer: C
Explanation:
Moving calculations to the data layer and materializing them in the extract can significantly improve the performance of reports in Tableau. The calculation ZN([Sales])*(1 - ZN([Discount])) is a basic calculation that can be easily computed in advance and stored in the extract, speeding up future queries. This type of calculation is less complex than table calculations or LOD expressions, which are better suited for dynamic analysis and may not benefit as much from materialization12.
References: The answer is based on the best practices for creating efficient calculations in Tableau, as described in Tableau's official documentation, which suggests using basic and aggregate calculations to improve performance1. Additionally, the process of materializing calculations in extracts is detailed in Tableau's resources2.
Given that all files share the same schema and have a common element in their file names, the wildcard union is an optimal approach to combine these files before performing any transformations. This strategy offers the following advantages:
Efficient Data Combination: Wildcard union allows multiple files with a common naming scheme to be combined into a single dataset in Tableau, streamlining the data preparation process.
Uniform Schema Handling: Since all files share the same schema, wildcard union ensures that the combined dataset maintains consistency in data structure, making further data manipulation more straightforward.
Pre-Transformation Combination: Combining the files before applying transformations is generally more efficient as it reduces redundancy in transformation logic across multiple files. This means transformations are written and processed once on the unified dataset, rather than repeatedly for each individual file.
References:
Wildcard Union in Tableau: This feature simplifies the process of combining multiple similar files into a single Tableau data source, ensuring a seamless and efficient approach to data integration and preparation.
NEW QUESTION # 40
A company has a sales team that is segmented by territory. The team's manager wants to make sure each sales representative can see only data relevant to that representative's territory in the team Sales Dashboard.
The team is large and has high turnover, and the manager wants the mechanism for restricting data access to be as automated as possible. However, the team does not have a Tableau Data Management license.
What should the consultant recommend to meet the company's requirements?
- A. Create a data source by joining the sales data table to an entitlements data table. Add a data source filter to restrict access and publish the data source. Connect the Sales Dashboard to this published data source.
- B. Create a user filter in the Sales Dashboard workbook and map each sales representative to the territories they are responsible for. Publish this dashboard to the Sales Dashboard project and ensure all users have permissions to view the dashboard.
- C. Create one group for each territory and assign sales representatives to the appropriate groups. Map each group to a territory in the Sales Dashboard. Publish this dashboard to the Sales Dashboard project and ensure all users have permissions to view the dashboard.
- D. Create separate workbooks for each territory. Publish each dashboard to the same Sales Dashboard project, and set permissions so each sales representative can see only the dashboards for their territories.
Answer: A
Explanation:
To ensure that each sales representative sees only data relevant to their territory, the best approach in the absence of a Tableau Data Management license involves using a joined data source with entitlements:
Data Source Configuration: Create a data source that joins the sales data table with an entitlements table. The entitlements table contains mappings of sales representatives to their respective territories.
Data Source Filter: Implement a data source filter that restricts data based on the current user's access rights. This filter references the joined entitlements to dynamically control data visibility based on the logged-in user.
Publishing the Data Source: Publish this filtered data source to Tableau Server. All workbooks or dashboards connecting to this data source inherently respect the row-level security established by the data source filter.
References
This approach aligns with Tableau's capabilities for implementing row-level security directly within the data source, as detailed in the Tableau security management and data modeling best practices.
NEW QUESTION # 41
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.
References
This 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 # 42
......
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