2024年08月13日合格確定ガイド準備TCC-C01試験知能問題集
無料最新Tableau Certified TCC-C01リアル試験問題と回答2024年更新
質問 # 34
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 of the workbooks connected to the data source are not visible to the user due to permissions.
- C. Some workbooks have been connected to the data source, but do not use any fields from it.
- D. Some workbooks have not been viewed by enough users yet.
正解：B
解説：
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.
質問 # 35
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?
- A. Select a previous version from Tableau Server, download it, and republish that data source.
- B. Delete and recreate the data source manually.
- C. Select a previous version from Tableau Server, and then click Restore.
- D. Request that a server administrator restore a Tableau Server backup.
正解：C
解説：
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.
質問 # 36
A client is using the Tableau Content Migration Tool to move content from an old Tableau Server to a new Tableau Server.
Which content will need to be moved using a different tool or process?
- A. Published data sources that use extracts
- B. Published data sources that use live connections
- C. Workbooks
- D. Tableau Prep flows
正解：D
解説：
When migrating content between Tableau servers, certain types of content may require special consideration or different tools for migration:
* Tableau Prep Flows: These are specific to Tableau Prep and are not included in the standard content migration capabilities of the Tableau Content Migration Tool. Tableau Prep flows often require separate processes for migration due to their distinct setup and integration with data sources and workflows.
* Published Data Sources and Workbooks: These can typically be migrated directly using the Tableau Content Migration Tool, which supports moving published data sources (both live connections and extracts) and workbooks without requiring additional tools.
References:
* Tableau Help and Support: Offers comprehensive tutorials and guidelines on using different tools for migrating various types of content, including the specific requirements for migrating Tableau Prep flows which are not covered by the standard content migration tool.
質問 # 37
From the desktop, open the CC workbook.
Open the Incremental worksheet.
You need to add a line to the chart that
shows the cumulative percentage of sales
contributed by each product to the
incremental sales.
From the File menu in Tableau Desktop, click
Save.
正解：
解説：
See the complete Steps below in Explanation:
Explanation:
To add a line showing the cumulative percentage of sales contributed by each product to the incremental sales in the Incremental worksheet of your Tableau Desktop, follow these detailed steps:
* Open the CC Workbook and Access the Worksheet:
* From the desktop, double-click on the CC workbook to open it in Tableau Desktop.
* Navigate to the Incremental worksheet by clicking on its tab at the bottom of the window.
* Calculate Cumulative Sales Percentage:
* Create a new calculated field to compute the cumulative percentage of sales. Right-click in the Data pane and select 'Create Calculated Field'.
* Name this field "Cumulative Sales Percentage".
* Enter the following formula to calculate the running sum of sales as a percentage of the total sales:
(RUNNING_SUM(SUM([Sales])) / TOTAL(SUM([Sales])) [Sales]))
* Click 'OK' to save the calculated field.
* Add the Cumulative Sales Percentage Line to the Chart:
* Drag the "Cumulative Sales Percentage" field to the Rows shelf, placing it next to the existing Sales measure.
* Ensure that the cumulative line appears as a continuous line. Right-click on the "Cumulative Sales Percentage" field on the Rows shelf, select 'Change Chart Type', and choose 'Line'.
* Adjust the axis to synchronize or dual-axis if necessary. Right-click on the axis of the
"Cumulative Sales Percentage" and select 'Synchronize Axis' if it's on a dual-axis setup.
* Format the Cumulative Sales Percentage Line:
* Click on the "Cumulative Sales Percentage" line in the visualization.
* Navigate to the 'Format' pane to adjust the line style, thickness, and color to make it distinct from other data in the chart.
* Save Your Changes:
* From the File menu, click 'Save' to ensure all your changes are stored.
References:
* Tableau Help: Provides additional details on creating calculated fields and customizing line charts.
* Tableau User Guide: Offers extensive instructions on formatting charts, including line types and axis synchronization.
By following these steps, you will successfully add a cumulative sales percentage line to your chart, enhancing the visualization to reflect the incremental contribution of each product to the overall sales in a dynamic and informative manner.
質問 # 38
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 wildcard Union option to combine/merge all the files together before doing the data transformation (calculations).
- B. Use join option to combine/merge all the files together before doing the data transformation (calculations).
- C. Apply the data transformation (calculations) in each require file and do the wildcard union to combine/merge before designing the visuals.
- D. Apply the data transformation (calculations) in each require file and do the join to combine/merge before designing the visuals.
正解：A
解説：
Moving calculations to the data layer and materializing them in the extract can significantly improve the performance of reports in Tableau. The calculationZN([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.
質問 # 39
A client currently has a workbook with the table shown below.
Which method will produce the output for the Total Sales Value field for all the categories shown in the table?
- A. A Window Function
- B. MAX() Function
- C. Level of Detail (LOD) Calculation
- D. Quick Table Calculation
正解：C
解説：
To calculate the Total Sales Value for all categories as displayed in the table, an LOD expression is ideal. An LOD calculation in Tableau allows you to compute values at the data level that is different from the view level. In this case, since the Total Sales Value appears consistent across different sub-categories within each category, an LOD expression can be used to fix the Total Sales Value irrespective of the sub-category detail.
Here's how to set it up:
* Go to the Calculations area by right-clicking in the data pane and selecting "Create Calculated Field".
* Enter a name for the calculation, such as "Total Sales Value".
* Enter the LOD expression:{ FIXED [Category] : SUM([Sales]) }. This calculation fixes the total sales to the category level, effectively summing sales for all sub-categories within each category, irrespective of how the data is broken down in the view.
* Drag this new calculated field into your visualization alongside the existing measures.
This method ensures that the Total Sales Value reflects the total for each category across all its sub-categories, matching the uniform values shown across different rows for each category in your table.
ReferencesThe explanation utilizes the concept of Level of Detail calculations in Tableau, which allows for advanced aggregations independent of the view level details. This concept is covered extensively in Tableau's official documentation and relevant training materials such as Tableau's online help resources.
質問 # 40
A client creates a report and publishes it to Tableau Server where each department has its own user group set on the server. The client wants to limit visibility of the report to the sales and marketing groups in the most efficient manner.
Which approach should the consultant recommend?
- A. Add user filters from Tableau Server to each worksheet and select only sales and marketing user groups.
- B. Grant access to the report on the Tableau Server only to the members of sales and marketing user groups.
- C. Use user groups defined on Tableau Server to build user filters in the report's data source.
- D. Prepare a row-level security (RLS) entitlement table to define limitations of the access and use it to build user filters in the report's data source.
正解：B
解説：
The most efficient way to limit report visibility to specific user groups on Tableau Server is to manage permissions directly on the server. By granting access to the report only to the sales and marketing user groups, the client ensures that only members of these groups can view the report. Thismethod is straightforward and does not require the additional steps involved in setting up row-level security or user filters.
References:The approach is supported by best practices in managing user permissions and visibility on Tableau Server, as described in the Tableau Community and official Tableau resources12.
質問 # 41
A Tableau Cloud client has requested a custom dashboard to help track which data sources are used most frequently in dashboards across their site.
Which two actions should the client use to access the necessary metadata? Choose two.
- A. Access metadata through the Metadata API.
- B. Connect directly to the Site Content data source within the Admin Insights project.
- C. Download metadata through Tableau Catalog.
- D. Query metadata through the GraphiQL engine.
正解：A、D
解説：
To track which data sources are used most frequently across a site in Tableau Cloud, the client should use the GraphiQL engine and the Metadata API.The GraphiQL engine allows for interactive exploration of the metadata, making it easier to construct and test queries1.The Metadata API provides access to metadata and lineage of external assets used by the content published to Tableau Cloud, which is essential for tracking data source usage2.
References:The actions are based on the capabilities of the GraphiQL engine and the Metadata API as described in Tableau's official documentation and learning resources321.
質問 # 42
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?
- A. {EXCLUDE [Customer ID]: COUNTD([Order ID])}
- B. {FIXED [Customer ID], [Region]: COUNTD([Order ID])}
- C. {INCLUDE [Customer ID]: COUNTD([Order ID])}
- D. {FIXED [Customer ID], [Region], [Order Date]: COUNTD([Order ID])}
正解：B
解説：
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.
質問 # 43
A company has a data source for sales transactions. The data source has the following characteristics:
. Millions of transactions occur weekly.
. The transactions are added nightly.
. Incorrect transactions are revised every week on Saturday.
The end users need to see up-to-date data daily.
A consultant needs to publish a data source in Tableau Server to ensure that all the transactions in the data source are available.
What should the consultant do to create and publish the data?
- A. Publish a live connection to Tableau Server.
- B. Publish an incremental refresh every Saturday.
- C. Publish an incremental extract refresh every day and publish a secondary data set containing data revisions.
- D. Publish an incremental extract refresh every day and perform a full extract refresh every Saturday.
正解：D
解説：
Given the need for up-to-date data on a daily basis and weekly revisions, the best approach is to use an incremental extract refresh daily to update the data source with new transactions. On Saturdays, when incorrect transactions are revised, a full extract refresh should be performed to incorporate all revisions and ensure the data's accuracy.This strategy allows end users to have access to the most current data throughout the week while also accounting for any necessary corrections12.
References:The solution is based on best practices for managing data sources in Tableau Server, which recommend using incremental refreshes for frequent updates and full refreshes when significant changes or corrections are made to the data12.
質問 # 44
Use the following login credentials to sign in
to the virtual machine:
Username: Admin
Password:
The following information is for technical
support purposes only:
Lab Instance: 40201223
To access Tableau Help, you can open the
Help.pdf file on the desktop.
From the desktop, open the CC workbook.
Open the Categorical Sales worksheet.
You need to use table calculations to
compute the following:
. For each category and year, calculate
the average sales by segment.
. Create another calculation to
compute the year-over-year
percentage change of the average
sales by category calculation. Replace
the original measure with the year-
over-year percentage change in the
crosstab.
From the File menu in Tableau Desktop, click
Save.
正解：
解説：
See the complete Steps below in Explanation:
Explanation:
To compute the required calculations and update the worksheet in Tableau Desktop, follow these steps:
* Compute Average Sales by Segment for Each Category and Year:
* Open the CC workbook and navigate to the Categorical Sales worksheet.
* Drag the 'Sales' field to the Rows shelf if it's not already there.
* Drag the 'Segment' field to the Rows shelf as well, placing it next to 'Category' and 'Year'.
* Right-click on the 'Sales' field in the Rows shelf and select 'Quick Table Calculation' > 'Average'.
This will compute the average sales for each segment within each category and year.
* Create a Calculation for Year-over-Year Percentage Change:
* Right-click in the data pane and select 'Create Calculated Field'.
* Name the calculated field something descriptive, e.g., "YoY Sales Change".
* Enter the formula to calculate the year-over-year percentage change:
(ZN(SUM([Sales])) - LOOKUP(ZN(SUM([Sales])), -1)) / ABS(LOOKUP(ZN(SUM([Sales])), -1))
* Click 'OK' to save the calculated field.
* Replace the Original Measure with the Year-over-Year Percentage Change in the Crosstab:
* Remove the original 'Sales' measure from the view by dragging it off the Rows shelf.
* Drag the newly created "YoY Sales Change" calculated field to the Rows shelf where the 'Sales' field was originally.
* Format the "YoY Sales Change" field to display as a percentage. Right-click on the field in the Rows shelf, select 'Format', and adjust the number format to percentage.
* Save Your Changes:
* From the File menu, click 'Save' to ensure all your changes are stored.
References:
* Tableau Help: Offers guidance on creating calculated fields and using table calculations.
* Tableau Desktop User Guide: Provides instructions on formatting and saving worksheets.
These steps allow you to manipulate data within Tableau effectively, using table calculations to analyze trends and changes in sales data by category and segment over years.
質問 # 45
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 in each view of each report using set filters and option Server/Create User Filter.
- C. 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.
- D. Create User filters based on data policies and apply them to a published data source.
正解：D
解説：
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.
質問 # 46
A consultant wants to improve the performance of reports by moving calculations to the data layer and materializing them in the extract.
Which calculation should the consultant use?
- A. POWER(ZN(SUM([Sales]))/
LOOKUP(ZN(SUM([Sales])), FIRST()),ZN(1/(INDEX()-1)))
- 1
END - B. SUM([Profit])/SUM([Sales])
- C. ZN([Sales])*(1 - ZN([Discount]))
- D. CASE [Sector Parameter]
WHEN 1 THEN "green"
WHEN 2 THEN "yellow"
正解：B
解説：
To improve performance by moving calculations to the data layer and materializing them in the extract, the consultant should choose calculations that benefit from pre-computation and significantly reduce the load during query time:
* Aggregation-Level Calculation: The formula SUM([Profit])/SUM([Sales]) calculates a ratio at an aggregate level, which is ideal for pre-computation. Materializing this calculation in the extract means that the complex division operation is done once and stored, rather than being recalculated every time the report is accessed.
* Performance Improvement: By pre-computing this aggregate ratio, Tableau can utilize the pre-calculated fields directly in visualizations, which speeds up report loading and interaction times as the heavy lifting of data processing is done during the data preparation stage.
References:
* Materialization in Extracts: This concept involves pre-calculating and storing complex aggregations or calculations within the Tableau data extract itself, improving performance by reducing the computational load during visualization rendering.
質問 # 47
From the desktop, open the CC workbook.
Open the City Pareto worksheet.
You need to complete the Pareto chart toshow the percentage of sales compared tothe percentage of cities. The chart mustshow references lines to visualize how thedata compares to the Pareto principle.
From the File menu in Tableau Desktop, clickSave.
正解：
解説：
See the complete Steps below in Explanation:
Explanation:
To complete the Pareto chart in the "City Pareto" worksheet of your Tableau Desktop and add reference lines to illustrate how the data compares to the Pareto principle, follow these steps:
* Open the CC Workbook and Access the Worksheet:
* From the desktop, double-click on the CC workbook to open it in Tableau Desktop.
* Navigate to the City Pareto worksheet by selecting its tab at the bottom of the window.
* Construct the Pareto Chart:
* Ensure that sales data is aggregated by city. If not, drag the 'City' dimension to the Columns shelf and the 'Sales' measure to the Rows shelf.
* Sort the sales data in descending order to properly align the cities according to their sales contribution.
* To create a running total of sales, right-click on the 'Sales' measure on the Rows shelf, select
'Quick Table Calculation', and choose 'Running Total'.
* Drag the 'Number of Records' field to the Rows shelf next to the Sales running total. Right-click on it, select 'Quick Table Calculation', and choose 'Running Total'. Set its calculation to 'Percent of Total' from the 'Edit Table Calculation' option to represent the percentage of cities.
* Add Reference Lines for the Pareto Principle:
* Click on the Analytics tab in the sidebar.
* Drag a 'Reference Line' element and drop it onto the chart area.
* Set the Reference Line for the Sales axis at 80% to represent the typical Pareto cutoff where 80% of effects come from 20% of causes.
* Add another Reference Line on the axis representing the percentage of cities, set at 20%, to visually assess the Pareto principle.
* Adjust the Appearance of the Chart:
* Format the reference lines by right-clicking on them, selecting 'Edit', and choosing a distinct style or color to make them stand out.
* Ensure the chart is clear and labels are appropriately adjusted for easy understanding of the data visualization.
* Save Your Changes:
* From the File menu, click 'Save' to ensure all your changes are stored.
References:
* Tableau Help: Offers detailed guidance on creating Pareto charts and adding reference lines.
* Tableau Visualization Best Practices: Provides tips on effectively displaying cumulative data and principles such as Pareto.
By following these steps, you will have successfully enhanced the City Pareto worksheet to include a complete Pareto chart with reference lines that illustrate how the sales data compares to the Pareto principle, making it easier to analyze and communicate the distribution of sales across cities.
質問 # 48
A client wants to produce a visualization to show quarterly profit growth and aggregated sales totals across a number of product categories from the data provided below.
Which set of charts should the consultant use to meet the client's requirements?
- A. Scatter plot and pie chart
- B. Waterfall chart and tree map
- C. Line and bubble charts
- D. Gantt and bar charts
正解：B
解説：
To effectively display quarterly profit growth and aggregated sales totals across different product categories, a combination of a Waterfall chart and a Tree Map is recommended:
* Waterfall Chart: This chart type is excellent for visualizing the sequential growth or decline of profits across different quarters for each sub-category. It clearly shows how profits accumulate over time, highlighting both positive and negative changes, which makes it ideal for tracking profit growth or decline through the quarters.
* Tree Map: A Tree Map can efficiently display aggregated sales totals where each block size represents the total sales of a product category, providing a quick, visually impactful comparison across categories.
This is especially useful when the client wants to understand which categories contribute most to sales in a glanceable format.
Together, these charts provide a comprehensive overview of both profit trends over time (Waterfall Chart) and a comparative snapshot of sales performance across categories (Tree Map), meeting the client's need to analyze performance dynamics in a detailed yet consolidated manner.
ReferencesThese recommendations are based on common best practices for data visualization in Tableau, where specific chart types are chosen for their strengths in communicating certain types of data relationships and dynamics, as detailed in Tableau's official visualization guides.
質問 # 49
A client wants to see data for only the last day in a dataset and the last day is always yesterday. The date is represented with the field Ship Date.
The client is not concerned about the daily refresh results. The volume of data is so large that performance is their priority. In the future, the client will be able to move the calculation to the underlying database, but not at this time.
The solution should offer the best performance.
Which approach should the consultant use to produce the desired results?
- A. Filter on calculation [Ship Date]=TODAY()-1.
- B. Filter on calculation [Ship Date]={MAX([Ship Date])}.
- C. Filter MONTH/DAY/YEAR on [Ship Date] field and use an option to filter to the latest date value when the workbook opens.
- D. Filter on Ship Date field using the Yesterday option.
正解：A
解説：
The best approach to ensure performance while providing data for only the last day (yesterday) in the dataset is to use a calculated field that filters the data to include only yesterday's date:
* Filter on calculation [Ship Date]=TODAY()-1: This calculated field dynamically computes yesterday's date by subtracting one day from today's date. This approach ensures that each day, only the data for the previous day is loaded, which keeps the volume of data minimal and improves performance.
* Dynamic Date Calculation: The use ofTODAY()-1ensures the filter remains up-to-date with the changing dates, without the need for manual updates, providing accuracy and timeliness in the dashboard.
This approach is efficient because it avoids the overhead of processing the entire dataset and focuses only on the relevant day's data. It also aligns with Tableau's capabilities for creating dynamic filters using date functions, as highlighted in the Tableau help documentation on date calculations and filters.
ReferencesThis solution utilizes Tableau's built-in date functions and dynamic calculations to optimize performance, as recommended in Tableau's performance optimization resources and date calculation guidelines.
質問 # 50
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?
- A. Split some visualizations on the dashboard into many smaller visualizations on the same dashboard.
- B. Connect to the data source via a custom SQL query.
- C. Restrict users from accessing the workbook to reduce server load.
- D. Use filters, hide unused fields, and aggregate values.
正解：D
解説：
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.
質問 # 51
A client is searching for ways to curate and document data in order to obtain data lineage. The client has a data source connected to a data lake.
Which tool should the consultant recommend to meet the client's requirements?
- A. Tableau Catalog with Tableau Data Management Add-on
- B. Tableau Catalog without Tableau Data Management Add-on
- C. Tableau Catalog with Tableau Server Management Add-on
- D. Tableau Prep Conductor
正解：A
解説：
To effectively curate and document data for obtaining data lineage, particularly from a data source connected to a data lake, the recommended tool is:
* Tableau Catalog with Tableau Data Management Add-on: This add-on enhances the capabilities of Tableau Catalog, providing extensive features for data management, including detailed data lineage, impact analysis, and metadata management.
* Functionality: The Tableau Catalog with the Data Management Add-on allows users to see the full history and lineage of the data, trace its usage across all Tableau content, and understand dependencies.
It also facilitates better governance and transparency in data handling.
* Why Choose this Tool: For a client needing comprehensive data lineage and documentation capabilities, this add-on ensures that data stewards and users can maintain and utilize a well-managed data environment. It supports robust data governance practices necessary for large and complex data ecosystems like those typically associated with data lakes.
ReferencesThe recommendation is based on the functionalities offered by the Tableau Data Management Add-on, as described in Tableau's official documentation on managing and documenting data sources for enhanced governance and operational efficiency.
質問 # 52
A client has a large data set that contains more than 10 million rows.
A consultant wants to calculate a profitability threshold as efficiently as possible. The calculation must classify the profits by using the following specifications:
. Classify profit margins above 50% as Highly Profitable.
. Classify profit margins between 0% and 50% as Profitable.
. Classify profit margins below 0% as Unprofitable.
Which calculation meets these requirements?
- A. IF([ProfitMargin]>=0.50,'Highly Profitable', 'Profitable')
ELSE 'Unprofitable'
END - B. IF [ProfitMargin]>0.50 Then 'Highly Profitable'
ELSEIF [ProfitMargin]>=0 Then 'Profitable'
ELSE 'Unprofitable'
END - C. IF [ProfitMargin]>=0.50 Then 'Highly Profitable'
ELSEIF [ProfitMargin]>=0 Then 'Profitable'
ELSE 'Unprofitable'
END - D. IF [ProfitMargin]>0.50 Then 'Highly Profitable'
ELSEIF [ProfitMargin]>=0 Then 'Profitable'
ELSEIF [ProfitMargin] <0 Then 'Unprofitable'
END
正解：C
解説：
The correct calculation for classifying profit margins into categories based on specified thresholds involves the use of conditional statements that check ranges in a logical order:
* Highly Profitable Classification: The first condition checks if the profit margin is 50% or more. This must use the ">=" operator to include exactly 50% as "Highly Profitable".
* Profitable Classification: The next condition checks if the profit margin is between 0% and 50%. Since any value falling at or above 50% is already classified, this condition only needs to check for values greater than or equal to 0%.
* Unprofitable Classification: The final condition captures any remaining scenarios, which would only be values less than 0%.
References:
* Logical Order in Conditional Statements: It is crucial in programming and data calculation to ensure that conditions in IF statements are structured in a logical and non-overlapping manner to accurately categorize all possible values.
質問 # 53
A client has several long-term shipping contracts with different vendors that set rates based on shipping volume and speed. The client requests a dashboard that allows them to model shipping costs for the next week based on the selected shipping vendor. Speed for the end user is critical.
Which dashboard building strategy will deliver the desired result?
- A. Aggregate the orders then use a calculated field that refers to a user-selected parameter to calculate the shipping costs.
- B. Calculate the potential shipping cost for each order with each vendor, display the aggregate costs in a large table, and use quick filters to limit the options visible to the user.
- C. Recommend that the client model for only profitability for the next 24 hours instead of a full week.
- D. Use a calculated field that refers to a user-selected parameter to calculate shipping costs for each order and then display the aggregate values.
正解：D
解説：
For modeling shipping costs based on varying vendor contracts and ensuring speed in dashboard performance, the suggested approach involves:
* Calculated Field with Parameter: Utilize a calculated field that dynamically references a user-selected parameter for the shipping vendor. This parameter adjusts the cost calculations based on selected vendor characteristics (like volume and speed).
* Aggregate Results: After calculating individual shipping costs, aggregate these costs to provide a concise, summarized view of potential expenses for the upcoming week. This method ensures the dashboard remains performant by reducing the load of processing individual line items in real-time.
* Why This Works: By using parameters and calculated fields, the dashboard can quickly adapt to user inputs without needing to re-query the entire dataset. Aggregating the results further improves performance and user experience by simplifying the output.
ReferencesThis strategy leverages Tableau's capability to handle dynamic calculations with parametersand is recommended for scenarios where performance and user-driven interaction are priorities. Tableau's performance optimization resources and dashboard design guidelines detail these techniques.
質問 # 54
A new Tableau user created a simple dashboard on Tableau Server using supply chain data. Now, the user wants to know if they created the dashboard in accordance with specific performance best practices.
Which approach should the consultant recommend for the client to make this determination?
- A. Use Performance Recording in Tableau Desktop.
- B. Run Workbook Optimizer.
- C. Use inbuilt dashboards in Tableau Server to troubleshoot the performance.
- D. Use Performance Recording on Tableau Server.
正解：B
解説：
The Workbook Optimizer is a tool specifically designed to evaluate a workbook against performance best practices. It provides feedback on key design characteristics and offers concrete guidance on how to improve workbook performance.This tool is beneficial for both new and experienced Tableau users to ensure their dashboards are optimized for performance1.
References:The Workbook Optimizer's functionality is detailed in Tableau's official documentation, which explains how it assesses workbooks against a set of rules derived from best practices1.Additionally, the Performance Recording feature in Tableau Desktop and Server can be used to identify performance issues, but the Workbook Optimizer gives a more comprehensive analysis of the workbook's adherence to best practices23.
質問 # 55
A client is using Tableau to visualize data by leveraging security token-based credentials. Suddenly, sales representatives in the field are reporting that they cannot access the necessary workbooks. The client cannot recreate the error from their offices, but they have seen screenshots from the field agents. The client wants to restore functionality for the field agents with minimal disruption.
Which step should the consultant recommend to accomplish the client's goal?
- A. Change the data source permissions for the connection to "Prompt User."
- B. Ask the workbook owners to republish the workbooks to refresh the security token.
- C. Renew the security token via the Data Connection on Tableau Server.
- D. Ensure that "Allow Refresh Access" was checked when the data source was published.
正解：C
解説：
When field agents are unable to access workbooks due to issues with security token-based credentials, the most immediate and least disruptive solution is to renew the security token. This can be done through the Data Connection settings on Tableau Server. Renewing the token will restore access for the field agents without requiring them to take any action or affecting other users.
References:The use of personal access tokens (PATs) in Tableau and the procedure for renewing them are documented in Tableau's official resources.It is noted that PATs are long-lived authentication tokens that can be revoked and renewed to manage access securely1.Additionally, there have been discussions in the Tableau Community regarding issues with concurrent PAT access, which further supports the need to manage tokens effectively2.
質問 # 56
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