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NEW QUESTION # 28
A client requests a published Tableau data source that is connected to SQL Server. The client needs to leverage the multiple tables option to create an extract. The extract will include partial data from the SQL Server data source.
Which action will reduce the amount of data in the extract?
- A. Use an extract filter.
- B. Set up the extract as an incremental refresh.
- C. Aggregate the extract to the visible dimensions.
- D. Define the filters by using custom SQL.
Answer: A
Explanation:
Using an extract filter is an effective way to reduce the amount of data in a Tableau extract. Extract filters allow you to specify a subset of the data to include, which can significantly decrease the size of the extract by excluding unnecessary data. This is particularly useful when you only need partial data from a larger SQL Server data source.
References: The recommendation to use extract filters to reduce data size is supported by Tableau's best practices for optimizing extracts. These practices suggest keeping the extract's data set short through filtering1. Additionally, discussions in the Tableau Community confirm that hiding fields and using extract filters before extracting data can help reduce the extract size2.
When dealing with large datasets in SQL Server and needing to create a manageable extract in Tableau, using an extract filter is the most direct and effective method to limit the data included:
Extract Filter: This involves setting filters that apply directly when the data is extracted from the source. This means that only the data meeting the specified criteria will be extracted and loaded into Tableau, significantly reducing the size of the extract.
To apply an extract filter, in the Data Source page in Tableau, drag the fields you want to filter by to the Filters shelf. Then, configure the desired filter criteria. When you create the extract, choose the option to "Add Filters to Extract" and select the configured filters. This ensures that only the data that meets these conditions is extracted from the SQL Server.
This approach not only minimizes the data volume but also speeds up performance in Tableau because it processes a smaller subset of the full dataset.
References
This procedure is described in detail in Tableau's help documentation on managing extracts and optimizing performance by using extract filters, which is recommended for scenarios involving large datasets or when specific subsets of data are required for analysis.
NEW QUESTION # 29
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. IF YEAR([Date])=2010 THEN {COUNTD ([OrderID])} END
- C. IF MIN(YEAR([Date]))=2010 THEN WINDOW_COUNTD([OrderID]) END
- D. COUNTD(IF YEAR([Date])=2010 THEN [OrderID] END)
Answer: D
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 the COUNTD function within an IF statement, which does not work as expected because the COUNTD function cannot conditionally count within the scope of the IF statement.
Correct Calculation: COUNTD(IF YEAR([Date]) = 2010 THEN [OrderID] END). This calculation checks each order date; if the year is 2010, it returns the OrderID. The COUNTD function then counts all unique OrderIDs 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.
References
This 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 # 30
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. Joining the tables in Tableau Prep
- B. Joining the tables in Tableau Desktop
- C. Relating the tables in Tableau Desktop
- D. Blending the first two tables with the third
Answer: C
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 # 31
A client notices that while creating calculated fields, occasionally the new fields are created as strings, integers, or Booleans. The client asks a consultant if there is a performance difference among these three data types.
What should the consultant tell the customer?
- A. Strings, integers, and Booleans all perform the same.
- B. Booleans are fastest, followed by integers, and then strings.
- C. Integers are fastest, followed by Booleans, and then strings.
- D. Strings are fastest, followed by integers, and then Booleans.
Answer: C
Explanation:
In Tableau, the performance of calculated fields can vary based on the data type used. Calculations involving integers and Booleans are generally faster than those involving strings. This is because numerical operations are typically more efficient for a computer to process than string operations, which can be more complex and time-consuming. Therefore, when performance is a consideration, it is advisable to use integers or Booleans over strings whenever possible.
References: The performance hierarchy of data types in Tableau calculations is documented in resources that discuss best practices for optimizing Tableau performance1.
NEW QUESTION # 32
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. Joining the tables in Tableau Prep
- B. Joining the tables in Tableau Desktop
- C. Relating the tables in Tableau Desktop
- D. Blending the first two tables with the third
Answer: C
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 # 33
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 - B. CASE [Sector Parameter]
WHEN 1 THEN "green"
WHEN 2 THEN "yellow" - C. ZN([Sales])*(1 - ZN([Discount]))
- D. SUM([Profit])/SUM([Sales])
Answer: D
Explanation:
END
Explanation:
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.
NEW QUESTION # 34
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. Renew the security token via the Data Connection on Tableau Server.
- C. Ask the workbook owners to republish the workbooks to refresh the security token.
- D. Ensure that "Allow Refresh Access" was checked when the data source was published.
Answer: B
Explanation:
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.
NEW QUESTION # 35
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. Use filters, hide unused fields, and aggregate values.
- C. Connect to the data source via a custom SQL query.
Answer: B
Explanation:
OD. Restrict users from accessing the workbook to reduce server load.
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 # 36
A client wants to provide sales users with the ability to perform the following tasks:
* Access published visualizations and published data sources outside the company network.
* Edit existing visualizations.
* Create new visualizations based on published data sources.
. Minimize licensing costs.
Which site role should the client assign to the sales users?
- A. Site Administrator
- B. Creator
- C. Explorer (can publish)
- D. Viewer
Answer: C
Explanation:
The Explorer (can publish) site role in Tableau is designed for users who need to access, edit, and create visualizations based on published data sources, even when they are outside the company network. This role allows users to perform web editing and save their work, making it suitable for sales users who need these capabilities. It is also a cost-effective option as it does not require the full capabilities and associated costs of the Creator license.
References: The information about the Explorer (can publish) role and its capabilities can be found in the official Tableau documentation on site roles and permissions12. This role is appropriate for users who need to interact with published content and create new visualizations without the need for full site administration or advanced content creation tools that come with the Creator role3.
NEW QUESTION # 37
A client notices that several groups are sharing content across divisions and are not complying with their data governance strategy. During a Tableau Server audit, a consultant notices that the asset permissions for the client's top-level projects are set to "Locked," but that "Apply to Nested Projects" is not checked.
The consultant recommends checking "Apply to Nested Projects" to enforce compliance.
Which impact will the consultant's recommendation have on access to the existing nested projects?
- A. Access will be automatically rolled back to the top-level project permissions immediately.
- B. Users will be notified that they will automatically lose access to content after 30 days.
- C. Users will be prompted to manually update permissions for all nested projects.
- D. Current custom access will be maintained, but new custom permissions will not be granted.
Answer: A
Explanation:
When "Apply to Nested Projects" is checked in Tableau Server, the permission rules set at the top-level project are enforced for all assets in the project and all nested projects. This means that any custom access previously granted to nested projects will be overridden, and the permissions will revert to those defined at the top-level project. This action ensures consistent application of the data governance strategy across all divisions.
References: The impact of checking "Apply to Nested Projects" is detailed in Tableau's official documentation, which explains how locked nested projects can be used to govern site content with greater flexibility and efficiency12.
NEW QUESTION # 38
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 # 39
SIMULATION
From the desktop, open the CC workbook. Use the US Population Estimates data source.
You need to shape the data in US Population Estimates by using Tableau Desktop. The data must be formatted as shown in the following table.
Open the Population worksheet. Enter the total number of records contained in the data set into the Total Records parameter.
From the File menu in Tableau Desktop, click Save.
Answer:
Explanation:
See the complete Steps below in Explanation
Explanation:
To shape the data in the "US Population Estimates" data source and enter the total number of records into the "Total Records" parameter in Tableau Desktop, 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 Population worksheet by selecting its tab at the bottom of the window.
Format and Shape the Data:
Ensure the data types match those specified in the requirements: Sex, Origin, Race as strings; Year, Age, Population as whole numbers.
To verify or change the data type, click on the dropdown arrow next to each field name in the Data pane and select "Change Data Type" if necessary.
Calculate Total Number of Records:
Create a new calculated field named "Total Records". To do this, right-click in the Data pane and select "Create Calculated Field".
Enter the formula COUNT([Record ID]) or SUM([Number of Records]) depending on how the data source identifies each row uniquely.
Drag this new calculated field onto the worksheet to display the total number of records.
Enter the Value into the Total Records Parameter:
Locate the "Total Records" parameter in the Data pane. Right-click on the parameter and select "Edit".
Manually enter the number displayed from the calculated field into the parameter, ensuring accuracy to meet the data shaping requirement.
Save Your Changes:
From the File menu, click 'Save' to ensure all your changes are stored.
References:
Tableau Desktop Guide: Provides detailed instructions on managing data types, creating calculated fields, and updating parameters.
Tableau Data Shaping Techniques: Outlines effective methods for manipulating and structuring data for analysis.
This process will ensure the data in the "US Population Estimates" is accurately shaped according to the specified format and that the total number of records is correctly calculated and entered into the designated parameter. This thorough approach ensures data integrity and accuracy in reporting.
NEW QUESTION # 40
A client has a pipeline dashboard that takes a long time to load. The dashboard is connected to only one large data source that is an extract.
It contains two calculated fields:
. TOTAL([Opportunities])
* SUM([Value])
It also contains two filters:
. A Relative Date filter on Created Date, a Date field containing values from 5 years ago until today
. A Multiple Values (Dropdown) filter on Account Name, a String field containing 1,000 distinct values A consultant creates a Performance Recording to troubleshoot the issue, and finds out that the longest-running event is "Executing Query." Which step should the consultant take to resolve this issue?
- A. Replace SUM([Value]) with WINDOW_SUM([Value]).
- B. Replace the TOTAL([Opportunities]) calculation with a Grand Total.
- C. Replace the Multiple Values (Dropdown) filter with a Multiple Values (Custom List) filter.
- D. Replace the Relative Date filter with a Multiple Values (Dropdown) filter on YEAR([Created Date]).
Answer: D
Explanation:
To improve the loading time of the pipeline dashboard, which primarily suffers from long query execution times due to a comprehensive Relative Date filter:
Relative Date Filter Issue: The existing Relative Date filter on "Created Date" covers a broad range (5 years), leading to significant data processing overhead as it includes granular date calculations over a large dataset.
Optimized Approach: By replacing the Relative Date filter with a Multiple Values (Dropdown) filter based on YEAR([Created Date]), the filter granularity is reduced. Filtering by year simplifies the query by limiting the volume of data processed and reducing the complexity of the filter condition.
Implementation Benefit: This approach still provides the flexibility to view data across different years but does so by reducing the load on the database during query execution, which is critical for improving the performance of the dashboard.
References
This recommendation aligns with Tableau performance optimization strategies, specifically regarding the management of date filters to minimize their impact on query load, as discussed in Tableau performance tuning sessions and guides.
NEW QUESTION # 41
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. Use a calculated field that refers to a user-selected parameter to calculate shipping costs for each order and then display the aggregate values.
- C. 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.
- D. Recommend that the client model for only profitability for the next 24 hours instead of a full week.
Answer: B
Explanation:
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.
References
This strategy leverages Tableau's capability to handle dynamic calculations with parameters and is recommended for scenarios where performance and user-driven interaction are priorities. Tableau's performance optimization resources and dashboard design guidelines detail these techniques.
NEW QUESTION # 42
A consultant plans a Tableau deployment for a client that uses Salesforce. The client wants users to automatically see Tableau views of regional sales filtered by customer as soon as the users sign into Salesforce.
Which approach should the consultant use to deliver the final visualization?
- A. Embed views into Salesforce.
- B. Publish to Tableau Mobile for viewing.
- C. Create subscriptions for each view to deliver reports by email.
- D. Create a list of URLs that the users can click in Salesforce.
Answer: A
Explanation:
To ensure that users automatically see Tableau views of regional sales filtered by customer as they sign into Salesforce, embedding the views directly into Salesforce is most effective:
Embedding Views: Tableau provides capabilities to embed its dashboards into web applications such as Salesforce. This approach ensures that the visualization is part of the Salesforce user interface, enhancing user experience by not requiring users to navigate away from Salesforce to view the data.
Implement this by using Tableau's embedding code, which can be generated from the Tableau Server for each specific view. Place this embed code into the Salesforce Visualforce pages or use Salesforce Canvas to integrate these views seamlessly.
This setup allows the Tableau views to inherit user credentials from Salesforce, enabling personalized data visualization based on the user's access rights and region, directly aligned with their Salesforce login session.
References
The embedding technique is documented in both Tableau's and Salesforce's official integration guides, which provide step-by-step instructions on embedding Tableau views into Salesforce platforms.
NEW QUESTION # 43
A client builds a dashboard that presents current and long-term stock measures. Currently, the data is at a daily level. The data presents as a bar chart that presents monthly results over current and previous years. Some measures must present as monthly averages.
What should the consultant recommend to limit the data source for optimal performance?
- A. Limit data to current and previous years, move calculating averages to data layer, and aggregate dates to monthly level.
- B. Limit data to current and previous years and leave data at daily level to calculate the averages in the report.
- C. Move calculating averages to data layer and aggregate dates to monthly level.
- D. Limit data to current and previous years as well as to the last day of each month to eliminate the need to use the averages.
Answer: A
Explanation:
For optimal performance, it is recommended to limit the data to what is necessary for analysis, which in this case would be the current and previous years. Moving the calculation of averages to the data layer and aggregating the dates to a monthly level will reduce the granularity of the data, thereby improving the performance of the dashboard. This approach aligns with best practices for optimizing workbook performance in Tableau, which suggest simplifying the data model and reducing the number of records processed12.
References: The recommendation is based on the guidelines provided in Tableau's official documentation on optimizing workbook performance, which includes tips on data management and aggregation for better performance12.
NEW QUESTION # 44
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. Quick Table Calculation
- B. MAX() Function
- C. A Window Function
- D. Level of Detail (LOD) Calculation
Answer: D
Explanation:
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.
References
The 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.
NEW QUESTION # 45
A multi-national company wants to have a Tableau dashboard that will provide country-level information for both its forecast summaries and year-on-year metrics. The company wants to toggle between these two views while leaving main key performance indicators (KPIs) visible on the main dashboard.
Which method is the most efficient in achieving the company's requirements?
- A. Create a parameter that accepts values from a list that contains "Forecast View" and "Year-on-Year View."
. Right-click the parameter and select Add to Sheet for both worksheets.
. Navigate back to the dashboard and to the upper corner of the two worksheets.
. Enable the Use as Filter option. - B. Create a single worksheet with all the measures required for both the forecast summary and the year-on-year views.
. Create a Boolean parameter and a corresponding calculated field with the following calculation: True.
. Add a blank dashboard object and in the Layout tab, check the box for "Control visibility using value" and select the parameter you created. - C. Create a dashboard with the sheets containing the main KPIs and the forecast summary worksheet.
. Duplicate this dashboard and replace the forecast view worksheet with the year-on-year metrics worksheet.
. Add navigation buttons to both dashboards. - D. Create a Boolean parameter with the two names of the views as aliases and a corresponding calculated field with the following calculation: True.
. Add the forecast summary sheet to the dashboard and add the year-on-year metrics sheet to the same dashboard as a Floating dashboard object.
Answer: D
Explanation:
. Add the calculated fields as a Detail under the Marks card of the floating view, create a "Change Parameter" action, and set the
"Target Parameter" and "Source Fields" to the parameter and calculated field you created.
. Check the box for "Control visibility using value" in the Layout tab of the floating view and select the parameter you created.
Explanation:
The most efficient method for toggling between two views (forecast summaries and year-on-year metrics) while keeping main KPIs visible involves using a parameter and calculated fields for controlling visibility:
Create a Boolean Parameter: This parameter will have two aliases representing the two views ("Forecast View" and "Year-on-Year View"). This allows the user to select which view they wish to see directly from the dashboard.
Calculated Field: Create a calculated field that always returns True. This field acts as a constant placeholder to enable the visibility control tied to the parameter.
Dashboard Setup: Place both the forecast summary and the year-on-year metrics sheets on the dashboard. Set the year-on-year metrics sheet as a floating object over the forecast summary.
Visibility Control: Use the "Control visibility using value" option in the Layout tab for the floating year-on-year metrics view. Tie this setting to the Boolean parameter so that changing the parameter will show or hide this view without affecting the main KPIs displayed on the dashboard.
Interactivity: Implement a "Change Parameter" dashboard action where selecting different options in the dashboard (e.g., clicking on certain parts) triggers the parameter to change, thus toggling the visible view.
References
This method leverages Tableau's dashboard interactivity features including parameters, calculated fields, and visibility settings, as recommended in Tableau's user guide on dynamic dashboard design.
NEW QUESTION # 46
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.
- A. New credentials were embedded into the data source.
- B. The dashboard was published to a different project.
- C. Tableau Server was upgraded.
- D. The dashboard was published with a new name.
Answer: B,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 # 47
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 MONTH/DAY/YEAR on [Ship Date] field and use an option to filter to the latest date value when the workbook opens.
- B. Filter on calculation [Ship Date]=TODAY()-1.
- C. Filter on Ship Date field using the Yesterday option.
- D. Filter on calculation [Ship Date]={MAX([Ship Date])}.
Answer: B
Explanation:
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 of TODAY()-1 ensures 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.
References
This 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.
NEW QUESTION # 48
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 inbuilt dashboards in Tableau Server to troubleshoot the performance.
- B. Use Performance Recording in Tableau Desktop.
- C. Run Workbook Optimizer.
- D. Use Performance Recording on Tableau Server.
Answer: C
Explanation:
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.
NEW QUESTION # 49
A consultant is designing a dashboard that will be consumed on desktops, tablets, and phones. The consultant needs to implement a dashboard design that provides the best user experience across all the platforms.
Which approach should the consultant take to achieve these results?
- A. Build one dashboard for each type of device and fix the size of the layouts.
- B. Build one dashboard and fix the size of the dashboard.
- C. Build one dashboard and set the size to Automatic.
- D. Build one dashboard that has desktop, tablet, and phone layouts, and fix the size of the layouts.
Answer: D
Explanation:
For a consultant designing a dashboard to be consumed across multiple device types, the best approach is:
Multi-device Layout: Tableau provides the capability to design device-specific layouts within a single dashboard. This feature allows the dashboard to adapt its layout to best fit the screen size and orientation of desktops, tablets, and phones.
Fixed Size Layouts: By fixing the size of each layout, the consultant can ensure that the dashboard appears consistent and maintains the intended design elements and user experience across devices. Fixed sizes prevent components from resizing in ways that could disrupt the dashboard's readability or functionality.
Implementation: In Tableau, you can create these layouts by selecting 'Device Preview' and adding custom layouts for each device type. Here, you define the dimensions and the positioning of sheets and controls tailored to each device's typical viewing mode.
References
This approach leverages Tableau's device designer capabilities, which are specifically designed to optimize dashboards for multiple viewing environments, ensuring a seamless user experience regardless of the device used. This functionality is well documented in Tableau's official guides on creating and managing device-specific dashboards.
NEW QUESTION # 50
A client wants to migrate their Tableau Server to Tableau Cloud. The Tableau Server is configured with three sites: Finance, Strategy, and Marketing. A consultant must provide a solution that minimizes user impact and costs.
Which configuration should the consultant recommend for Tableau Cloud to meet the client's requirements?
- A. One Tableau Cloud instance configured with a Finance project folder, Strategy project folder, and Marketing project folder
- B. Three separate Tableau Cloud instances for Finance, Strategy, and Marketing
- C. One Tableau Cloud instance with two sites for Strategy and Marketing, and one Tableau Server instance for Finance
- D. One Tableau Cloud instance configured with all workbooks in a single project
Answer: A
Explanation:
To minimize user impact and costs while migrating from Tableau Server to Tableau Cloud with multiple sites, the best solution is:
Single Tableau Cloud Instance with Multiple Projects: Instead of multiple sites which could imply higher management overhead and possibly higher costs, configuring one Tableau Cloud instance with different project folders for each former site (Finance, Strategy, Marketing) is most efficient.
Benefits: This setup maintains organizational separation of data and access similar to having different sites but leverages the unified management and simplicity of a single cloud instance. It reduces complexity in user access management and integration points.
Implementation: Each project folder acts like a mini-site within the larger instance, where specific permissions and content can be managed independently, akin to the original server setup but within a single cloud-based environment.
References
This recommendation is in line with best practices for cloud migration focusing on consolidation and cost efficiency, as suggested in Tableau's official documentation for cloud migration strategies.
NEW QUESTION # 51
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